# Full Text: DopamineForaging

> Extracted from `2018_DopamineForaging.pdf`

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Research
Cite this article: Ingram KK, Gordon DM,
Friedman DA, Greene M, Kahler J, Peteru S.
2016 Context-dependent expression of the
foraging gene in field colonies of ants:
the interacting roles of age, environment
and task. Proc. R. Soc. B 283: 20160841.
http://dx.doi.org/10.1098/rspb.2016.0841
Received: 14 April 2016
Accepted: 5 August 2016
Subject Areas:
behaviour, ecology
Keywords:
foraging gene, social insect, task allocation,
division of labour
Author for correspondence:
Krista K. Ingram
e-mail: kingram@colgate.edu
Electronic supplementary material is available
at http://dx.doi.org/10.1098/rspb.2016.0841 or
via http://rspb.royalsocietypublishing.org.
Context-dependent expression of the
foraging gene in field colonies of ants:
the interacting roles of age, environment
and task
Krista K. Ingram1, Deborah M. Gordon2, Daniel A. Friedman2, Michael Greene3,
John Kahler1 and Swetha Peteru4
1Department of Biology, Colgate University, 13 Oak Drive, Hamilton, NY 13346, USA
2Department of Biology, Stanford University, Gilbert Biological Science Building, Stanford, CA 94305, USA
3Department of Integrative Biology, University of Colorado, Campus Box 171, PO Box 176634, Denver,
CO 80217-3364, USA
4Department of Geography, Texas A&M University, College Station, TX 77843, USA
KKI, 0000-0002-4512-1549; DAF, 0000-0001-6232-9096
Task allocation among social insect workers is an ideal framework for study-
ing the molecular mechanisms underlying behavioural plasticity because
workers of similar genotype adopt different behavioural phenotypes. Elegant
laboratory studies have pioneered this effort, but field studies involving
the genetic regulation of task allocation are rare. Here, we investigate the
expression of the foraging gene in harvester ant workers from five age- and
task-related groups in a natural population, and we experimentally test how
exposure to light affects foraging expression in brood workers and foragers.
Results from our field study show that the regulation of the foraging gene in
harvester ants occurs at two time scales: levels of foraging mRNA are associated
with ontogenetic changes over weeks in worker age, location and task, and
there are significant daily oscillations in foraging expression in foragers. The
temporal dissection of foraging expression reveals that gene expression changes
in foragers occur across a scale of hours and the level of expression is predic-
ted by activity rhythms: foragers have high levels of foraging mRNA during
daylight hours when they are most active outside the nests. In the experimental
study, we find complex interactions in foraging expression between task behav-
iour and light exposure. Oscillations occur in foragers following experimental
exposure to 13 L : 11 D (LD) conditions, but not in brood workers under similar
conditions. No significant differences were seen in foraging expression over
time in either task in 24 h dark (DD) conditions. Interestingly, the expression
of foraging in both undisturbed field and experimentally treated foragers is
also significantly correlated with the expression of the circadian clock gene,
cycle. Our results provide evidence that the regulation of this gene is
context-dependent and associated with both ontogenetic and daily behavio-
ural plasticity in field colonies of harvester ants. Our results underscore the
importance of assaying temporal patterns in behavioural gene expression
and suggest that gene regulation is an integral mechanism associated with
behavioural plasticity in harvester ants.
1. Introduction
One of the most exciting new frontiers in sociogenomics is investigating how
behavioural plasticity in advanced social organisms is regulated by molecular
mechanisms [1–7]. Social insects provide an ideal system for studying the evol-
ution and ecology of behavioural plasticity because the ecological success of a
colony depends on task allocation [2,3,8,9]. Colonies operate without central
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control. Individuals respond to local cues; and in the aggregate,
the colony adjusts the numbers of workers performing various
tasks, in response to current conditions [10]. Recent molecular
studies present evidence for strong links between differential
gene regulation and worker development [11,12], behaviour
[7,13–16] and social environment [13,15,17,18]. These studies,
in conjunction with the sequencing of many social insect
genomes [19–27], provide the critical groundwork for detailed
functional analysis of target genes and their effect on social
insect behaviour.
Task allocation differs among social insect species. In many
social insect societies, workers progress through tasks in an
age-dependent manner, a process termed temporal polyethism
[28]. Diverse mechanisms, using conserved molecular path-
ways, interact to regulate age-polyethism in workers [3].
For example, genetic pathways involved in nutrition and
metabolism play a major role in the regulation of worker task
(reviewed in [3,29]). Causal relationships between gene
regulation and age-related transitions in worker task have
been documented for malvolio, a gene involved in manganese
transfer and sucrose responsiveness [30], the storage protein
gene, vitellogenin [31], the insulin-signalling TOR pathway
[32,33] and foraging, a cyclic GMP-activated protein kinase
[34–36]. The results from these studies highlight the complex-
ity of relationships between conserved genetic pathways and
transitions to foraging in social insects.
The foraging gene, a cGMP-activated protein kinase gene
(PKG), has emerged as a behavioural gene of particular interest
due to the diversity of relationships between the expression of
this gene and behaviour [14,29,34,37–45]. Foraging is associ-
ated with behaviour in diverse taxa including nematodes,
insects and mammals [40,44]. However, associations between
this gene and behaviour vary across species in both mechanism
and proposed function, ranging from learning and memory
to chemotaxis and food-related behaviours [40,44]. PKG is
activated by a common secondary messenger (cGMP) and,
when activated, phosphorylates a host of cellular proteins
[46]. Thus, this gene is associated with a diverse range of
behavioural and physiological processes [44].
The foraging gene was originally described in fruit flies [37]
and has been shown to have a direct link to foraging behaviour
in several insect species [34,35,37,43]. foraging has also been
shown to influence habituation and sucrose responsiveness,
stress tolerance, olfactory and visual learning, memory and
sleep patterns in fruit flies [47–49].
In social insects, the foraging gene is implicated in the age-
related transition from other tasks to foraging [34,35,39,42,
43,50]. In honeybees, Polistes metricus wasps and Bombus terres-
tris bumblebees, foragers have higher levels of expression of
foraging than nurse bees [32,34,50]. By contrast, studies on
Vespula wasps, Bombus ignites bumblebees and harvester ants
suggest that workers that forage have lower levels of foraging
mRNA than workers that do not forage [39,42,43,51]. Similarly,
the ant Pheidole pallidula shows high activity of this gene in the
soldier caste and low expression in minor workers that engage
frequently in foraging [43]. Interestingly, an experimental
manipulation of same-age cohorts and tasks in Cardiocondyla
obscurior
demonstrated
that
foraging
expression
in
this
short-lived ant is correlated with age, but not with the foraging
task [52].
Here, we explore foraginggeneexpressionandtask allocation
in a natural population of red harvester ants (Pogonomyrmex
barbatus). In previous work, we showed that the expression of
a harvester ant orthologue (Pbfor) to foraging at dawn was
lower in foragers than workers of other tasks, including brood
care (nurse) workers [39]. Harvester ants live in large colonies
of up to 12 000 workers in the southwestern deserts of the
United States [53]. Temporal polyethism in harvester ants
occurs over the course of a year, the approximate lifespan of a
worker [54,55]. Younger workers perform tasks related to
brood care and do not leave the nest. Workers then progress to
nest maintenance work, with brief trips out of the nest to carry
out refuse, then to patrolling, with short morning forays from
the nest, and finally to foraging [56–58]. Foragers spend the
most time out of the nest, leaving in early morning and foraging
until mid-afternoon.
In the field, foraging activity occurs in a daily temporal
pattern [59,60]. The discovery of task-specific expression of
circadian clock genes in harvester ants confirmed that fora-
gers have a functional molecular clock and endogeneous
circadian rhythms, while workers that perform tasks inside
the nest do not show pronounced circadian rhythms in
activity levels or expression of clock genes [61]. In addition,
results from a laboratory study on Pogonomyrmex occidentalis,
a congener of P. barbatus, revealed that the expression of the
foraging gene in workers can vary with time of day [62].
Foragers of P. occidentalis had low levels of foraging mRNA
only during late evening and early morning hours, and had
high levels of foraging mRNA relative to non-foraging
workers during the daytime. These laboratory results led us
to question whether the previous finding of low foraging
gene expression in P. barbatus foragers was influenced by
the early morning collection time of the field samples.
Here, we explore how gene expression correlates with the
temporal regulation of foraging behaviour in a natural popu-
lation of harvester ants. By investigating gene expression as it
occurs in the field, we are able to investigate the molecular
responses to the natural cues of temperature, light and inter-
actions among workers [63–66] that influence the circadian
pattern of foraging activity. We consider two time scales,
asking how foraging expression is associated with daily indi-
vidual activity rhythms during a circadian cycle, and how
the patterns of expression are associated with task transitions
over weeks to months as workers mature. In addition, we
experimentally manipulate the light conditions of field-
collected brood workers and foragers to test whether the
expression of foraging is correlated with exposure to light and
the expression of the circadian clock gene, cycle.
2. Material and methods
(a) Ant collection
Workers of P. barbatus were collected from colonies near our long-
term study site in Rodeo, New Mexico. To ensure representation of
all behavioural tasks and to replicate findings across colonies,
workers were collected from large, mature colonies in the early
morning hours (n ¼ 4 colonies for field study, n ¼ 6 colonies for
experimental study). Workers were designated as belonging to
one of five groups: callows, brood workers, nest maintenance,
patrollers or foragers, defined as in previous work [58,60]. We con-
sidered three age-related worker categories: immature workers
(called callows) and two of the task groups (brood care workers
and foragers) which represent clear transitions in the maturation
of workers. Two other tasks (patrolling and nest maintenance)
are more labile, so are less tightly associated with worker age
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[57,58]. Patrollers, foragers and, to a lesser extent, nest maintenance
workers are exposed to external environmental conditions [67].
Patrollers, which were the first group we collected in the
morning, emerge at first light and travel around the nest
mound and foraging area, often with the abdomen tucked
under the thorax [68]. Patrollers stimulate the start of foraging
upon returning to the nest and influence the direction of foraging
each day. Nest maintenance workers make short trips outside the
nest to carry out debris and discard it in a pile away from the nest
entrance. Newly emerged adults (callows) are identified by their
distinct orange-coloured exoskeleton. In laboratory colonies, cal-
lows are usually found near the brood and queen, and may
participate in brood work [58]. Brood care workers are young
workers that are found inside brood chambers. We collected
only brood care workers that were carrying brood in their
mandibles. Foragers were collected in late morning, while they
were returning to the nest carrying food. The nests were then
excavated to collect the brood workers and callows.
(b) Field experiment set-up for time of day sampling
Callows and brood workers were placed together in 30.5 
30.5 cm plastic boxes with sand and brood in complete darkness.
Nest maintenance and patrollers were placed in plastic boxes
with sand and rocks that were dark on one side and exposed to
ambient light on the other side; foragers were placed in plastic
boxes with sand and grasses, and half of the box was exposed to
ambient light. The boxes were housed in ambient temperature con-
ditions in a laboratory at the Southwestern Research Station
(American Museum of Natural History) in Portal, Arizona. To con-
trol for potential effects of alarm responses induced during the
transport of ants to the laboratory, we made certain that all task
groups were exposed to the same handling conditions. In the
course of the subsequent 24 h, a sample of 4–5 ants from each
task and colony were removed at 4 h intervals, and flash frozen
in liquid nitrogen. All sampling during evening hours was done
using dim red light in dark conditions. Ants were collected from
each colony at seven time points: 16.00, 20.00, 24.00, 4.00, 8.00,
12.00 and 16.00 (day 2). Approximate daylight hours during
sampling were 13 h of daylight (5.30–18.30). Frozen ants were
stored in the 2808C freezer prior to brain dissection.
(c) Light exposure experiment
Foragers and brood workers (n ¼ 18 workers per task per colony)
were collected from six medium-sized field colonies as described
above. Workers were immediately placed into artificial nest-boxes
(n ¼ 24 nest-boxes in total) in one of two treatments: 13 L : 11 D
(LD) ants were placed in nest-boxes (with water ad libitum) with
ambient daytime light and night-time darkness; DD ants were
housed in identical nest-boxes in complete darkness for 24 h.
Nest-boxes with inside workers contained some dirt/sand and
brood from the original colony. Forager nest-boxes contained
some dirt/sand and local leaves. Workers were sampled from
these artificial nest-boxes at three time points (13.00, 21.00 and
5.00). Red lights were used to sample during the dark hours to mini-
mize light exposure. Live workers were placed immediately into
cryovials and then flash frozen in liquid nitrogen. Frozen samples
were stored on dry ice, shipped to Colgate University and frozen
at minus 808C prior to brain dissection.
(d) RNA extraction and quantitative real-time PCR
Brains were dissected on dry ice and placed immediately into
RNAlater (Ambion) to remove glands. Whole brains (including
optic lobes) were placed immediately in lysis buffer and hom-
ogenized with Qiashedders (Qiagen). RNA was purified from
three homogenized brains per sample using RNAeasy Micro
Kit (Qiagen) protocols. Purified RNA was frozen at 808C prior
to qPCR procedures. Harvester ant-specific primers for qPCR
analyses were designed from exon-coding regions to amplify a
128 bp region of foraging using the newly sequenced genome
[22,23]. cDNA was synthesized from extracted total RNA preps
using ABI TaqMan Gold Reverse Transcriptase reagents and
random hexamers. The 10 ml reactions included 1.0 ml of RNA
with 1 TaqMan RT Buffer, 5.5 mM MgCl2, 500 uM of each of
the deoxyNTPs, 2.5 uM of the random hexamer primers,
0.4 U ml21 of RNase Inhibitor and 1.3 U ml21 of MultiScribe
Reverse Transcriptase (50 U ml21). Each colony had one sample
(n ¼ 3 brains) per time point; reactions were performed in tripli-
cate for each sample (n ¼ 3 technical replicates). All reactions
were run at 258C for 10 min, 488C for 30 min and 958C for
5 min, and then stored at 2208C until quantitative PCR. For
each cDNA replicate, expression of Pbfor was assayed on an
ABI 7900 HT instrument using ABI Taqman Gold reagents and
primers
designed
as
a
Taqman
Gene
Expression
Assay
(table 1). The 25 ml qPCR reactions for foraging included 3.5 ml
of template cDNA with 1 TaqMan Buffer A, 5.5 mM MgCl2,
200 mM each of dNTPs, 100 nM of probe, 200 nM of each
primer, 0.01 U ml21 of AmpErase UNG and 0.025 U ml21 of
AmpliTaq Gold DNA Polymerase (50 U ml21). To standardize
foraging expression, elongation factor 1a (64 bp) was used as a con-
trol for each cDNA replicate. Of the three control genes tested
(PbEF1a, Pb18S and PbRPII), the amplification efficiency of
PbEF1a was most similar to the foraging gene and levels of
PbEF1a did not vary over time. The 25 ml qPCR reactions for
the control included 1.5 ml of template cDNA. For the light
exposure experiment, expression of the cycle gene was also
measured with the same procedure used for foraging expression.
Real-time PCR reactions for Pbfor and PbEF1a were performed
under the following conditions: 2 min at 508C for one cycle, 10 min
at 958C for one cycle, 15 s at 958C, 1 min at 588C, for 45 cycles. Data
were analysed using SDS 2.1 software and quantification of rela-
tive mRNA levels was calculated using the DDCt method. For
the field experiment, relative expression levels within colonies
were calculated across all tasks and time points, and then normal-
ized (due to potential differences in gene expression levels across
colonies) using a z-score transformation. For both treatments in
the light experiment, relative expression levels within colonies
were calculated across both foraging and brood care tasks for com-
parisons of overall foraging expression between tasks. Relative gene
expression was also calculated within tasks in each treatment
to compare changes in expression over time for each task.
(e) Statistical analysis
To test for differences in individual brain expression levels among
groups, we tested for normality using Shapiro–Wilk tests in SPSS.
Because the data did not deviate significantly from a normal distri-
bution, we used mixed-model ANOVAs with time as the ‘within
Table 1. qPCR primers designed for study.
gene
forward primer
reverse primer
probe
PbFor
TGGTGGTGACCCAATGAAGACGTA
GTTCCGCGGGATTATCTCTG
TCCATCACGCGTAACGCAATGGCT
PbCYCix
GCGATATGCAGGTGAAAGAAGA
ATCACGCAATACTTCCAATCTATGTT
CGACACCACCATTGGCTGTCACAGA
PbEF1a
GGCTCTGAGGGAGGCTTT
CGGAGATGTTCTTCACGTTGAA
CTCGCGATAACGTCG
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subject’ fixed factor, task, location or age as ‘between subjects’
fixed factors, and colony as a random factor. For the field study,
we tested three hypotheses. We tested whether foraging gene
expression was associated with task by comparing the five behav-
ioural tasks. We tested whether foraging gene expression was
associated with worker environment by comparing internal
workers (callows and brood care workers) to external workers
(nest maintenance, patrollers and foragers). We tested whether
foraging gene expression was associated with worker age by com-
paring callows (newly emerged), brood care workers (young
workers) and foragers (old workers).
Differences in the pattern of relative Pbfor expression over
time were analysed for individual task groups using mixed-
model ANOVAs. We also tested the pattern of Pbfor expression
in foragers using repeated measures contrast analyses [69].
Contrast analysis tests specific, theoretically driven, a priori pre-
dictions about patterns in repeated measures data. We tested
the prediction that daily fluctuations in foraging gene expression
follow observed daily rhythms in task behaviour. The expression
pattern of foragers was compared with a generalized sinusoidal
curve that approximates the daily foraging activity rhythms of
harvester ant foragers in the field and the locomotor activity of
foragers in laboratory colonies. We used Pearson’s correlation
analyses to test the correlation of foraging and cycle expression
within each task.
To test for differences in foraging expression in the light
exposure experiment, we used mixed-model ANOVAs with time
as the ‘within subject’ fixed factor, light condition as the ‘between
subjects’ fixed factor and colony as a random factor. We tested
within-task differences in expression over time of day with one-
way ANOVAs. We used Pearson’s correlation analyses to test the
correlation of foraging and cycle expression in foragers in LD and
DD conditions. All analyses were performed in SPSS and
we controlled for multiple testing using Bonferroni corrections.
3. Results
(a) Field study
When considering all five tasks, gene expression varies signifi-
cantly among tasks (F4,98 ¼ 3.732, pcorr ¼ 0.021, h2 ¼ 0.132;
figure 1 and table 2), and the interaction between task and
time was significant (F2,98 ¼ 2.521, pcorr ¼ 0.003, h2 ¼ 0.09).
Comparisons of internal and external tasks (callows and
brood
care
workers
versus
nest
maintenance
workers,
–2.0
–1.5
–1.0
relative foraging expression (z-score by colony)
–0.5
0
0.5
1.0
1.5
2.0
callows
16
20
0
4
8
12
16(2)
16
20
0
4
8
12
16(2)
brood workers
nest maintenance
patrollers
foragers*
–2.0
–1.5
–1.0
–0.5
0
0
0.5
1.0
1.5
2.0
–2.0
–1.5
–1.0
–0.5
0
0.5
1.0
1.5
2.0
–2.0
–1.5
–1.0
–0.5
0
0.5
1.0
1.5
2.0
–2.0
–1.5
–1.0
–0.5
0.5
1.0
1.5
2.0
16
20
0
4
8
12
16(2)
16
20
0
4
8
12
16(2)
16
20
0
4
8
12
16(2)
Figure 1. Relative gene expression levels of foraging across time (hours) from field-collected workers of five behavioural tasks. Relative expression values for each
data point represent the average expression level across colonies (n ¼ 4 colonies, +s.e.). Data were normalized to account for differences in the amplitude of gene
expression between colonies using a z-score transformation; thus, relative expression values are plotted as the number of standard deviations above and below the
mean value for all data points (across task and time). Standard error bars are calculated from variation across four colonies. The open stripe in the horizontal bar at
base of the plot represents the daylight phase (13 h) and the solid stripe represents the dark phase (11 h) during the night. Overall differences in foraging gene
expression among tasks are significant; only foragers have significantly different levels of Pbfor mRNA over time. *p , 0.05. (Online version in colour.)
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patrollers and foragers) revealed significant differences in gene
expression between locations (F1,118 ¼ 7.895, pcorr ¼ 0.006,
h2 ¼ 0.062), and the interaction between location and time
was
significant
(F6,118 ¼ 4.943,
pcorr ¼ 0.000,
h2 ¼ 0.201).
When considering only age-related categories (young callows
and brood care workers versus older foragers), gene expression
varied significantly across age (F2,62 ¼ 14.277, pcorr ¼ 0.000,
h2 ¼ 0.315) and the interaction between age and time was
significant (F6,62 ¼ 9.899, pcorr ¼ 0.000, h2 ¼ 0.489).
Foragers
have
significant
changes
in
foraging
gene
expression over time (F6,20 ¼ 3.613, pcorr ¼ 0.019, h2 ¼ 0.520;
other tasks, see electronic supplementary material, table
S1). The pattern of expression of Pbfor mRNA in forager
brains is correlated with the generalized sinusoidal function
curve predicted from the daily fluctuations in foraging
behaviour (t ¼ 2.78, r ¼ 0.89, p ¼ 0.05). Expression levels of
Pbfor were significantly correlated with cycle expression in
foragers only (foragers: Pearson’s correlation ¼ 0.80, p ¼
0.03; other tasks, see electronic supplementary material,
table S2).
(b) Light exposure experiment
In the exposure experiment, we found significant differences
in relative gene expression for task (F1,57 ¼ 9.141, pcorr ¼
0.004, h2 ¼ 0.138), but not for light condition (F1,57 ¼ 0.058,
pcorr ¼ 0.810, h2 ¼ 0.001), time of day (F1,57 ¼ 1.643, pcorr ¼
0.202, h2 ¼ 0.055) or the interaction between task and light
condition (F1,57 ¼ 0.011, pcorr ¼ 0.916, h2 ¼ 0.000; figure 2
and table 3).
When relative expression is calculated within tasks across
time of day, foragers differ in foraging levels depending on
time of day only in the LD treatment, but this difference is
not significant following correction for multiple tests (LD:
F2,9 ¼ 2.859,
pcorr ¼ 0.109,
h2 ¼ 0.389;
DD:
F2,10 ¼ 0.982,
pcorr ¼ 0.408, h2 ¼ 0.164; figure 3). Foraging expression in
foragers is significantly correlated with the expression of cycle,
a circadian clock gene in LD (Pearson’s correlation ¼ 0.627,
p ¼ 0.007) and DD (Pearson’s correlation ¼ 0.633, p ¼ 0.005)
conditions. Brood workers do not show differences in foraging
expression depending on time of day in either treatment (LD:
F2,9 ¼ 0.670,
pcorr ¼ 0.536,
h2 ¼ 0.130;
DD:
F2,15 ¼ 0.765,
pcorr ¼ 0.483, h2 ¼ 0.092).
4. Discussion
The temporal dissection of foraging expression in harvester ants
reveals that the regulation of this gene is associated with
worker behaviour at two time scales. On the scale of hours,
gene expression undergoes changes greater than twofold, in
magnitude, during the daily activity rhythms of foragers. On
the scale of weeks to months, a shift in the daily temporal pat-
tern of gene expression occurs during worker ontogeny from
young workers inside the nest to older foragers. The temporal
patterns of foraging gene expression in harvester ants are
associated with worker task, age, location and exposure to
light. Thus, our results reveal a complex gene  physiology 
environment interaction, as would be expected for a behav-
iour-related gene that is one component of an intricate
network. These associations are driven by significant fluctu-
ations of Pbfor expression in workers of a particular task,
foraging. Of the five worker groups studied, only foragers
show significant daily fluctuations in foraging gene expression.
The regulation of this gene in foragers is associated with daily
activity patterns. Foragers have relatively higher expression
during the day, when they are most active outside the nest,
collecting food.
Table 2. Mixed-model ANOVA results for field study. We tested three hypotheses: the effect of task, location or age and time of day on foraging expression
in workers.
d.f.
F
p-valuesa
h2
task
task
4,98
3.732
0.021*
0.132
time
6,98
0.699
0.651
0.041
task  time
24,98
2.521
0.003**
0.090
location
location
1,118
7.895
0.006**
0.062
time
6,118
1.010
0.422
0.049
location  time
6,118
4.943
0.000*
0.201
age
age
2,62
14.277
0.000**
0.315
time
6,62
1.475
0.201
0.125
age  time
6,62
9.899
0.000**
0.489
aBonferroni-corrected p-values; *p , 0.05, **p , 0.01.
–1.0
–0.5
0
0.5
1.0
1.5
BC
FOR
BC
FOR
DD
LD
relative foraging expression (z-score)
5.00
13.00
21.00
Figure 2. Results from the light exposure experiment. Gene expression data
were measured across all samples and were transformed using a z-score analysis
across colonies (n ¼ 6) to control for differences in expression levels between
colonies. Bars represent the number of standard deviations above or below the
mean colony expression value (+s.e.). Differences between tasks are signifi-
cant; there is no significant effect of light condition or task  light
interaction on expression levels. BC ¼ brood care workers; FOR ¼ foragers;
LD ¼ 13 h ambient light exposure, 11 h dark; DD ¼ continuous 24 h dark.
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Our field results demonstrate an increase in foraging
expression when foragers are most actively foraging outside
the nest, exposed to light and other external environmental
cues. However, nest maintenance workers and patrollers are
also exposed to external conditions, although for a shorter
amount of time than foragers, but these workers do not
show significant diurnal changes in foraging expression. For-
agers
in
laboratory
colonies
of
a
related
species,
P.
occidentalis, also had high levels of foraging mRNA during
the day [62]. This increase in foraging expression in harvester
ant foragers may be associated with exposure to new external
stimuli when the worker begins to forage, including exposure
to light, and the rapid learning associated with foraging be-
haviour [44]. The fact that gene expression does not change
significantly over time for either nest maintenance workers
or patrollers in field colonies suggests that if external factors
do indeed influence the foraging pathway, the duration of
exposure to the external environment may be important.
Our experimental results support the hypothesis that
exposure to light may modulate foraging expression in fora-
gers but not brood workers. Expression levels of the
foraging gene are depressed in foragers relative to brood
workers in time points representing the dark phase of the
LD treatment and are relatively low, and with more variabil-
ity, in the DD treatment. Previous laboratory experiments on
honeybees established a causal link between foraging gene
expression, and foraging behaviour and suggested a potential
role for foraging in phototaxis [34,35]. Differences in photo-
taxis between tasks have not yet been adequately tested in
harvester ants. If Pbfor expression is linked to phototactic
behaviour, then it is reasonable to expect that the levels of
Pbfor in nest maintenance workers and patrollers would be
similar to forager levels during their active hours outside
the nest, but this was not the case in our study.
Alternatively, harvester ant foragers possess strong mol-
ecular circadian rhythms [61], and this internal clock may be
linked to the regulation of behavioural genes involved in task
allocation. The association of the circadian clock with the regu-
lation of the foraging gene gains support in this study from both
behavioural and molecular data. In rhythmic foragers, the
expression of Pbfor is correlated with daily behavioural pat-
terns and with the expression of the clock gene, cycle, in both
field and experimental conditions. Arrhythmic brood workers
do not have differences in foraging expression with time of day,
even when exposed to LD conditions. However, foragers typi-
cally maintain rhythms and cyclic expression of cycle in DD
(data not shown), while we do not see significant differences
in foraging expression under DD conditions in this study.
These results suggest that foraging expression is modulated
by the extended exposure to hours of light or other external fac-
tors, and is not simply influenced by endogenous rhythms.
Another possibility is that significant oscillations in foraging
expression are too difficult to measure given the weak circadian
oscillations in DD conditions, a phenomenon also seen in some
circadian genes.
Daily oscillations in the foraging gene were also evident in
a microarray analysis of circadian rhythms in honeybee fora-
gers, although subsequent qPCR analyses did not detect
significant variation over time for either nurses or foragers
[15]. The molecular pathways affected by circadian circuitry
are not yet well understood, but recent work emphasizes
multiple molecular responses to oscillations in circadian
genes that are related to behaviour [15,70–73].
Our results highlight the importance of considering the
effect of time on sampling expression levels of behavioural
genes, particularly those that are likely to be closely linked
to circadian rhythms. In harvester ants, daytime levels of
foraging mRNA can be higher in foragers relative to other
task groups, but at some times of day, foragers exhibit
lower expression levels of foraging than other task groups.
This finding has two implications. First, brood workers and
callows have relatively greater expression during late evening
and early morning hours. This explains why, in a previous
study in which ants were sampled at dawn [39], foraging
expression was lower in foragers relative to other task
groups. Second, our results indicate that some of the reported
experimental differences among species in the patterns of
foraging expression may not represent distinct associations
of foraging gene expression with species-specific behaviour.
Instead, differences in the timing of sample collections may
lead to the inadvertent capture of discrete snapshots of
expression levels across the daily fluctuations in expression
of the gene. Our review of the methods in previous studies
of social insects [34–36,42,43,50,52] did not provide enough
detail on the timing of sampling to determine how much
this may have influenced the results.
One limitation of this field study is that it is not possible to
completely disentangle the effects of age from the effects of
–1.0
–0.5
0
0.5
1.0
1.5
relative foraging expression (z-score)
5.00
13.00
21.00
LD
DD
Figure 3. Expression levels of foraging mRNA differ with time of day in LD
but not DD conditions in foragers. Bars represent relative gene expression
calculated across foragers only. Data were transformed using a z-score analysis
across colonies (n ¼ 6) to control for differences in expression levels between
colonies. Relative expression values are plotted as the number of standard
deviations above and below the mean colony value for foragers (+s.e.).
LD ¼ 13 h ambient light exposure, 11 h dark; DD ¼ continuous 24 h dark.
Table 3. Mixed-model ANOVA results for experimental study. We tested
one hypothesis: the effects of light condition (LD or DD) and time of day
on foraging expression in workers.
d.f.
F
p-values
h2
task
1,57
9.141
0.004**
0.138
light condition
1,57
0.058
0.810
0.001
time
2,57
1.643
0.202
0.055
task  light
1,57
0.011
0.916
0.000
task  time
2,57
0.558
0.576
0.019
light  time
2,57
0.401
0.671
0.014
task  light  time
2,57
0.585
0.560
0.020
**p , 0.01.
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## Page 7

location and/or task. Because ants probably perform nest
maintenance and patrolling across a range of ages, and some
may overlap with ages of foragers, experiments would be
needed using similar-age cohorts that perform different
tasks. This has been done in elegant laboratory experiments
on social insects (e.g. [34,52]) but would be difficult to do in
a natural field experiment.
Gene expression and the presence of foraging mRNA do
not
necessarily
translate
to
protein
activity
differences
in vivo. Future experiments should examine expression pat-
terns in FOR protein in brains of foragers versus workers of
other task groups. Additionally, in situ studies of RNA
levels will elucidate whether the differential regulation of
foraging is limited to particular brain areas in particular task
groups, or during particular stages of behavioural matu-
ration. A study of the ant Pheidole pallidula indicates that the
spatial distribution of the foraging protein in the brain differs
between minor and major workers of this species [43]. Thus,
there may be changes in the location of foraging-sensitive
regions of the brain involved in the transitions between
tasks in harvester ant workers that could be determined by
immunohistochemical analyses.
The flexibility in the regulation of foraging expression
underscores the potential importance of this gene in the
development of behavioural plasticity in social insect workers
[45]. The foraging gene is highly conserved in the Hymenop-
tera, with little evidence for functional evolution in amino
acid sequence [62]. It appears that gene regulation is the inte-
gral mechanism associated with behavioural plasticity, at
least in harvester ants. The growing body of work showing
that the amino acid-encoding sequences of many genes affect-
ing social behaviour are highly conserved opens an exciting
new direction in sociogenomics [2,3,74]—to understand
when and where these conserved genes are active and how
these differences play a role in organizing behaviour. Our
results emphasize the importance of understanding how
gene expression influences behaviour in natural field environ-
ments as well as in laboratory settings. Understanding the
diversity of mechanisms by which conserved molecular path-
ways regulate behavioural plasticity in workers is a central
issue in social insect biology and is critical to unravelling
the molecular organization of social behaviour.
Data accessibility. Primer information and datasets supporting this article
are available on Dryad database (doi:10.5061/dryad.nj811) [75].
Authors’ contributions. K.K.I. designed research, performed genetic and
statistical analyses, and wrote the manuscript. S.P., M.G., D.M.G. and
D.A.F. planned and participated in field collections. S.P. and J.K. per-
formed brain dissections and expression analyses. K.K.I., D.M.G.,
M.G. and D.A.F. contributed to further revisions of the manuscript.
Competing interests. The authors confirm that they have no competing
interests.
Funding. This work was supported by a Picker Interdisciplinary Science
Research Grant to K.K.I. and a National Science Foundation Integrative
Organismal Systems (NSF-IOS) Facilitating Research at Primarily
Undergraduate Institutions (RUI) grant to K.K.I. (IOS-1021723).
Acknowledgements. We would like to thank Shelby Sturgis for assistance
in field collections, Brett Ford and Susannah Stolz for help with brain
extractions and gene expression assays, and Ahmet Ay and Allan
Filipowicz for assistance in statistical analysis.
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---
*Extraction method: pymupdf*