# Full Text: DistributedPhysiology

> Extracted from `2020_DistributedPhysiology.pdf`

---

## Page 1

Contents lists available at ScienceDirect
Hormones and Behavior
journal homepage: www.elsevier.com/locate/yhbeh
Review article
Distributed physiology and the molecular basis of social life in eusocial
insects☆
D.A. Friedmana,⁎, B.R. Johnsona,1, T.A. Linksvayerb,1
a University of California, Davis, Department of Entomology, Davis, CA 95616, United States of America
b University of Pennsylvania, Department of Biology, Pennsylvania, PA 19104, United States of America
A R T I C L E I N F O
Keywords:
Eusocial
Insect
Colony
Molecular
Physiology
Evolution
Hormones
Development
Caste
Task
A B S T R A C T
The traditional focus of physiological and functional genomic research is on molecular processes that play out
within a single multicellular organism. In the colonial (eusocial) insects such as ants, bees, and termites, mo-
lecular and behavioral responses of interacting nestmates are tightly linked, and key physiological processes are
regulated at the scale of the colony. Such colony-level physiological processes regulate nestmate physiology in a
distributed fashion, through various social communication mechanisms. As a result of physiological decen-
tralization over evolutionary time, organismal mechanisms, for example related to pheromone detection, hor-
mone signaling, and neural signaling pathways, are deployed in novel contexts to inﬂuence nestmate and colony
traits. Here we explore how functional genomic, physiological, and behavioral studies can beneﬁt from con-
sidering the traits of eusocial insects in this light. We highlight functional genomic work exploring how nest-
mate-level and colony-level traits arise and are inﬂuenced by interactions among physiologically-specialized
nestmates of various developmental stages. We also consider similarities and diﬀerences between nestmate-level
(organismal) and colony-level (superorganismal) physiological processes, and make speciﬁc hypotheses re-
garding the physiology of eusocial taxa. Integrating theoretical models of distributed systems with empirical
functional genomics approaches will be useful in addressing fundamental questions related to the evolution of
eusociality and collective behavior in natural systems.
1. Introduction
Division of labor and collective behavior underlie the ecological
success of eusocial species such as ants, termites, and honey bees
(Ward, 2014; Korb, 2016). Eusocial species are those that live in co-
lonies with multiple overlapping generations, with nestmates partici-
pating in brood care, nest building, foraging, and defense (Wilson and
Hölldobler, 1988; Hölldobler and Wilson, 2009; Linksvayer, 2015).
Eusocial species exhibit colony traits, such as collective foraging and
defense (Wray et al., 2011; Gordon, 2013; Gordon et al., 2013), which
are either absent or rudimentary in solitary insects.
Division of labor (DOL) refers to variation among eusocial insect
nestmates in behavior, morphology, and physiology (Hölldobler and
Wilson, 2009; Goldsby et al., 2014; Jeanne, 2016; Gordon, 2016a;
Pasquaretta and Jeanson, 2018). In its most complex form, referred to
as a caste system, the colony is composed of groups of nestmates that
vary strongly in their reproductive potential and task performance. As
Wilson, Hölldobler, and Seeley pointed out, the most elaborate forms of
DOL lead to workers with limited information about the activities of the
rest of the colony (Wilson and Hölldobler, 1988; Hölldobler and Wilson,
2009). Extensive signaling among specialized nestmates ensures a unity
of purpose at the superorganismal (colony) level (Durand et al., 2019).
Seeley referred to these signaling mechanisms among nestmates as
“social physiology” (Seeley, 2009). Building on this concept of social
physiology, Johnson and Linksvayer (Gordon, 2016a) argued that DOL
is composed of two parts: Social Anatomy and Social Physiology.
Social anatomy is analogous to specialized anatomy (e.g., organs, tis-
sues) in a metazoan body, while social physiology plays the analogous
role to organismal physiology in a metazoan body.
Social anatomy refers to colonies being composed of specialized
parts with limited roles, like the organs of an animal organism (Fig. 1).
Under certain conditions, this specialized colony anatomy allows for
greater productivity and eﬃciency in the completion of many tasks
(Waibel et al., 2006; Cooper and West, 2018; Gillooly et al., 2010;
https://doi.org/10.1016/j.yhbeh.2020.104757
Received 31 October 2019; Received in revised form 30 March 2020; Accepted 6 April 2020
☆This paper belongs to special issue VSI: Behavioral Genomics.
⁎ Corresponding author at: One Shields Avenue, 383 Briggs Hall, Davis, CA 95616, United States of America.
E-mail address: DanielAriFriedman@gmail.com (D.A. Friedman).
1 These authors contributed equally to the work.
Hormones and Behavior 122 (2020) 104757
Available online 22 April 2020
0018-506X/ © 2020 Elsevier Inc. All rights reserved.
T

## Page 2

Burgess et al., 2017). Specialization exists at multiple levels within the
colony. A primary distinction in the colony is between male and female
nestmates (Beani et al., 2014). Queens are females with high re-
productive output; workers are females with zero or very low re-
productive output. Queen-worker reproductive skew allows for an in-
creased reproductive output of queens alongside increased work output
from workers, with both castes usually developing from the same di-
ploid female genome (Ratnieks et al., 2011). Eusocial species vary
widely in their total size, ratio of diﬀerent classes of nestmates, and
extent of subspecialization within the worker caste. Variation within
and among classes of worker nestmates can manifest as variation in
body size or allometry (Abouheif et al., 2014), and also is typiﬁed by
temporal polyethism, the stereotyped process by which workers change
in behavior and physiology as they age and in response to experiences
(Gordon, 1989; Tripet and Nonacs, 2004; Johnson, 2010; Yan et al.,
2014).
Both
morphological
and
temporal
specializations
among
workers are reﬂected by extensive tissue-speciﬁc physiological changes
that facilitate specialization by each age group (Walsh et al., 2018).
Social physiology is the set of dynamic mechanisms that co-
ordinate the activity and development of the specialized parts of the
colony (Fig. 1). The principles of colony physiology are broadly the
same as the principles of organismal physiology (e.g. homeostasis,
balance of anabolism/catabolism, nutrient partitioning among tissues),
as colonies are complex adaptive systems that are targets of colony-
level selection (Linksvayer, 2015; Birch and Okasha, 2015; Okasha,
2016). Whether colonies successfully grow and produce new queens
and males that can start the next generation depends on coordination
and function at the colony level. Thus it is not surprising that in many
species, colony-level traits (e.g. architecture, foraging behavior) have
been found to either directly inﬂuence colony-level productivity (i.e.
production of workers and reproductives), or inﬂuence other ecologi-
cally-important aspects of colony function (Wilson, 1968; Anderson and
Ratnieks, 1999).Colony physiological processes transfer information
among nestmates and include both physical interactions (vibrations and
tactile contact) and molecular signaling (Fielde and Parker, 1904;
Johnson and Linksvayer, 2010; Leonhardt et al., 2016). Molecular
signaling mechanisms are varied and include volatile and nonvolatile
pheromones (Leonhardt et al., 2016; Bortolotti and Costa, 2014; Stökl
and Steiger, 2017), as well as the direct transfer of bioactive compounds
such as small RNAs, proteins, hormones, and nutrients (LeBoeuf et al.,
2013; LeBoeuf et al., 2016; Maori et al., 2019).
Here we use a eusocial physiology framework to review empirical
research on how organismal and colony-level physiological processes
diﬀer, interact, and co-evolve (Linksvayer, 2015; Seeley, 2009; Johnson
and Linksvayer, 2010). The eusocial physiology framework considers
how specialized components of the eusocial insect colony (social
anatomy) interact to regulate key nestmate and colony traits (social
physiology). We describe how the eusocial physiology framework leads
to novel insights into how to best explore the genetics, evolution, and
physiology of the eusocial insects.
2. Similarities between colony and organismal anatomy
physiology
The concept of social anatomy (and similarly, the concept of the
superorganism) has been criticized because in some eusocial insect
species there is little queen-worker dimorphism, or because re-
productive and physical castes demonstrate phenotypic plasticity at
various scales (Jeanne, 2016; Gordon, 2016a; Gordon, 1989; Canciani
et al., 2019). However there is a similar variation among taxa in the
extent of germ-soma separation and plasticity in multicellular organ-
isms, for example the extremely variable cases of plants, worms,
sponges, and bilaterians (Winston, 2010; Gilbert et al., 2012; Neuhof
et al., 2016; Colgren and Nichols, 2019; Sugden, 2000). Multicellular
organisms vary considerably in size, degree of anatomical specializa-
tion, reproductive life history, and sophistication of physiological reg-
ulatory mechanisms. Similarly there is great variation among eusocial
taxa in the complexity of their social anatomy (the extent of speciali-
zation among nestmates) and social physiology, and also their re-
productive life history (Ward, 2014; Gordon, 2016b).
Colony and organismal physiology are both dynamic processes that
play out via regulatory interactions involving neural and molecular
mechanisms and various tissue types (Fig. 1). In organismal physiology,
regulatory processes that are distributed among tissues coordinate be-
havior with cellular metabolism. For example in Drosophila neural and
hormonal signals in the brain are in feedback with hormone signaling in
gut and fat cells, leading to co-regulation of foraging behavior with fat
cell metabolism (Liu and Jin, 2017; Musselman and Kühnlein, 2018). In
the eusocial colonies, the coordination of foraging behavior with fat
metabolism is also regulated by multi-tissue feedback loops. In the
eusocial colony, larvae brain-fat-gut neurohormonal feedback loops are
tightly linked to brain-fat-gut feedback loops in adult nestmates
(Linksvayer, 2015; Johnson and Linksvayer, 2010). Multi-tissue phy-
siological processes, whether in multicellular organisms or colonial
Fig. 1. Organismal and eusocial colony physiology. Organisms regulate their body physiology via neural and molecular mechanisms. In eusocial insect colonies,
physiological mechanisms include these neural and molecular types, as well as the physical interactions among colony members. The regulation of nestmate and
colony traits arises from interactions within and across castes, task groups, and developmental stages.
D.A. Friedman, et al.
Hormones and Behavior 122 (2020) 104757
2

## Page 3

superorganisms, are mediated by diﬀusible signaling molecules. In or-
ganismal physiology, internal ﬂuids carry diﬀusible factors. These
ﬂuids include hemolymph (insects), as well as blood, lymph, and other
ﬂuids (mammals). In the eusocial insect colony, there is sharing of
diﬀusible signaling molecules through the air (volatile compounds),
through liquid solvents (through trophallaxis), as well as via the solid
phase (deposition of long-lasting pheromone compounds on the ground
allowing stigmergy). In sum, the hormonal and neurobiological me-
chanisms involved in the regulation of foraging in eusocial insects share
many functional and genomic similarities with analogous systems in
solitary insects (Friedman and Gordon, 2016; Kamhi et al., 2017; Nässel
and Zandawala, 2019). The key diﬀerence is that the senders and the
receivers of the information are in diﬀerent metazoan bodies in the
eusocial colony, as opposed to interactions among diﬀerent tissues in a
single metazoan body.
3. Anatomical and physiological innovations of superorganisms
In insects, physiological processes generally occur within single cells
via signaling molecules (Tsuruyama, 2018), within multicellular orga-
nismal bodies via endocrine signaling (Rose and Mian, 2015; Stark and
Theodoridis, 1973), and among insect bodies via exocrine signaling
(Leonhardt et al., 2016; Stökl and Steiger, 2017). To facilitate social
physiology (colony-level coordination of action) social insects have
evolved radically new functions for conserved tissues and also novel
tissues. For example, ant workers have more than 75 distinct exocrine
glands, secreting hundreds of diverse molecular compounds (Hölldobler
and Wilson, 2009; Billen, 1991; Hölldobler et al., 2014; Cerdá et al.,
2014; d'Ettorre, 2016). Other eusocial insects show similarly complex
exocrine systems, for example honey bees use hundreds of exocrine
compounds; the physiological mechanisms and colony-level implica-
tions have been investigated for a small subset of these molecules
(Bortolotti and Costa, 2014; Alaux et al., 2010).
The exocrine secretory mechanisms of insect colonies have become
embedded within colony-level distributed physiological processes,
meaning they are playing a fundamentally endocrine (internal reg-
ulatory) role within the colony. Whether one considers colony pher-
omones as exocrine compounds (from the perspective of the insect body
glandular structure) or as colony-level endocrine compounds (from the
perspective of the colony as an organism), there are key similarities
between the inﬂuence of pheromones on colony members and hor-
mones on organs. Both colony pheromones and organismal hormones
result in large-scale behavioral changes via tissue-speciﬁc physiological
manipulation, often acting in feedback loops, or at very low doses or
slow time-scales (Stökl and Steiger, 2017; Khoury et al., 2013;
Invernizzi and Ruxton, 2019). Reproductive signaling between the
queen and workers are an obvious example of this, as is signaling from
the brood to the foragers. In honey bees, for example, larvae secrete
brood pheromones that stimulate foraging behavior and inﬂuence for-
ager brain gene expression (Pankiw et al., 1998; Traynor et al., 2015;
Ma et al., 2019). Essentially, foragers do not forage when they are
hungry (mediated by conserved regulators of hunger signaling in soli-
tary insects (Friedman and Gordon, 2016; Kaun and Sokolowski, 2009;
Favreau et al., 2018)), but as a result of stimuli from other nestmates
(Razin et al., 2013; Silberman et al., 2016; Davidson et al., 2016;
Feinerman and Korman, 2017). The neurophysiological basis of reward,
decision-making, and foraging are at least largely conserved across both
eusocial and solitary insects (Friedman and Gordon, 2016; Perry and
Barron, 2013; Søvik et al., 2015; Anreiter and Sokolowski, 2019),
highlighting that evolutionary shifts in the relevance of diﬀerent in-
ternal and external stimuli (e.g. internal hunger cues vs. brood signals)
can lead to drastic changes in how the behavior (nursing or foraging) is
deployed.
Colony traits, such as the elaborate foraging biology mediated by
the dance language system in honey bees (Bortolotti and Costa, 2014;
Perry et al., 2015; Lemanski et al., 2019) or the fungal agricultural
practices of leaf cutting ants (Schultz and Brady, 2008; Aylward et al.,
2012), are based on extensive signaling among nestmates. While many
researchers have emphasized the importance of conﬂict within eusocial
societies (Cooper and West, 2018; Birch and Okasha, 2015; Okasha,
2016; Quiñones et al., 2020; Almond et al., 2019), we suggest that these
colony-level signaling mechanisms that underlie social physiological
processes are largely honest in nature and have evolved mainly through
colony-level selection. This is in contrast signaling mechanisms in
simpler animal societies and solitary organisms, where conﬂict and
deceptive signaling may predominate, as a result of individual-level
selection. We suggest that the evolutionary elaboration of eusociality is
an evolutionary trajectory that allows for runaway collaborative sig-
naling
rather
than
largely-adversarial
tit-for-tat
signaling
games
(Hölldobler and Wilson, 2009; Leonhardt et al., 2016; Holman, 2012).
Even in the most conﬂict prone contexts, such as egg laying (where
there is strong potential for conﬂict, i.e. within-colony selection, in
some species between multiple queens or between queens and
workers), socially complex societies likely practice largely honest
communication, because dishonest communication is likely very costly
at the colony level. Honest signaling of fertility is found in honey bees
and several ant species (Oi et al., 2015; Villalta et al., 2018). In Lasius
niger and other eusocial insect species, the queen(s) signals her fertility
honestly even when that fertility is substandard and leads to her ex-
ecution (Holman, 2012; Holman et al., 2013)(however in other ants and
bees, see (Katzav-Gozansky et al., 2001; Liebig et al., 1999; Ratnieks
and Visscher, 1989)).
4. Social physiology: hormonal mechanisms and evolutionary
consequences
Exemplifying the distributed nature of colony physiology, some
hormonal processes that are mediated internally in other insects may
fall under the control of another task group within obligately eusocial
colonies. While the basic players of the physiological processes may
remain the same, there may be a spatial reorganization of signaling so
that regulation is enacted across multiple insect bodies. For example,
foraging behavior and fat metabolism are linked through integrated
neurohormonal mechanisms in Drosophila (Kaun and Sokolowski,
2009), such that ﬂies forage when hungry and stop feeding when full.
Eusocial insect colonies must also balance foraging behavior with fat
metabolism and food reserves, with an additional challenge: the fora-
ging behavior is performed by an entirely disjoint set of nestmates
(foragers) from those engaged in fat metabolism (larvae). These beha-
viorally- and physiologically-specialized components of the colony en-
gage in cross-regulation using behavioral interactions (Davidson et al.,
2016; Wainselboim et al., 2002; Rivera et al., 2015) and molecular
signaling (Ma et al., 2019; Perry et al., 2015). The exact mechanics of
the physiological distribution in the eusocial insect colony will depend
on species-speciﬁc colony structure and life history. For example,
stingless bees seal larvae into cells with provisions, while ants and
honey bees feed brood continuously through the larval instars. These
diﬀerences among eusocial taxa in the modes of nutrient processing
should be associated with major adaptive shifts in larval and adult
metabolism.
In social insects, there can be a fundamental rewiring and turnover
of the physiological processes that were present in their solitary an-
cestors. The evolution of eusociality is often directly compared to other
major lineage-speciﬁc transitions in evolution (e.g. prokaryote →eu-
karyote, unicellular life→multicellular life (Wilson and Hölldobler,
1988; Szathmáry and Smith, 1995; Szathmáry, 2015)). Insect species
that are eusocial reﬂect the outcome of basic insect physiology (e.g.
ancestral body plan, conserved gene families) overlaid with novel su-
perorganismal
regulatory
mechanisms
(social
anatomy
and
phy-
siology). Simply by joining together into a social group, additional
possible regulatory mechanisms can be enacted by non-eusocial insects
at the group level (Ramdya et al., 2015; Ramdya et al., 2017), such
D.A. Friedman, et al.
Hormones and Behavior 122 (2020) 104757
3

## Page 4

mechanisms become reﬁned and elaborated in the eusocial insects
(Linksvayer, 2015; Leonhardt et al., 2016; Friedman and Gordon, 2016;
Feinerman and Korman, 2017; Marshall et al., 2009). Here we consider
several ways in which gene regulatory networks have been shaped
during the transition toward eusociality, and during subsequent
lineage-speciﬁc evolution of colony traits.
Several studies suggest that there is increased complexity of
genomic regulatory mechanisms in eusocial insects (e.g., increased
number of transcription factors or CREs (Yan et al., 2014; Simola et al.,
2013; Shields et al., 2018)), as well as lineage-speciﬁc gains and losses
of major families of transposable elements (Wissler et al., 2013;
Rubenstein et al., 2019; Petersen et al., 2019). Over evolutionary time,
genes and signaling molecules can be gained or lost from regulatory
networks. Gene regulatory networks can evolve via the addition of
signaling hubs from other ancestral signaling networks through new
connections (more common as per EvoDevo model (Wagner and Zhang,
2011)), resulting in novel phenotypes (Eksi et al., 2018). Alternatively,
gene regulatory networks can grow in social insect genomes by in-
tegrating novel (taxonomically-restricted) genes, facilitated by the fact
that younger genes are apparently under less transcriptional co-
ordination at the level of organs (Jasper et al., 2015; Johnson and
Jasper,
2016)
and
nestmate
caste
distinctions
(Mikheyev
and
Linksvayer, 2015; Warner et al., 2019a). It appears that gene regulatory
networks evolve through both changes in the regulation of conserved
loci and incorporation of new players: novel loci are more likely to be
incorporated into distal parts of gene regulatory networks and be ex-
pressed in novel or secretory tissues, while conserved loci are more
likely to undergo changes to transcriptional regulation in conserved
tissues (Jasper et al., 2015; Feyertag et al., 2017).
The function of conserved members of physiological regulatory
processes can be inﬂuenced by sequence changes, new regulatory
connections, or other contextual changes. For example, the cGMP-de-
pendent protein kinase G enzyme (known as foraging in Drosophila) is
well-studied in the context of foraging and metabolic regulation across
vertebrate and invertebrate taxa (Struk et al., 2019; Wang and
Sokolowski, 2017; Anreiter et al., 2017). While the homology of the
PKG locus is indeed deeply conserved, the action of PKG is cell-type
speciﬁc and also probably depends on the identity of downstream
phosphorylation targets. Hence there is not a consistent role or direc-
tion of eﬀect for PKG even across just Hymenoptera (Wenseleers et al.,
2008; Heylen et al., 2008; Lucas and Sokolowski, 2009; Ingram et al.,
2011; Ingram et al., 2016; Malé et al., 2017). Thus while PKG may play
a role in foraging-related physiological networks of diverse insects,
there are species-speciﬁc changes to the inputs & outputs of PKG such
that the function of over- or under-expression of PKG cannot be reliably
predicted, even locally. Similar claims could be made for conserved
gene families such as pigmentation/neurotransmitter-related genes that
play roles in regulating worker behavior (Kamhi et al., 2017; Signor
et al., 2016), and conserved neuropeptides that have gained task-spe-
ciﬁc functions (Gospocic et al., 2017; Chandra et al., 2018). Recent
evidence suggests that genetic pathways involved in generating sexu-
ally dimorphic morphology and behavior in solitary insects (e.g. dsx/
fru/tra (Verhulst and van de Zande, 2015; Millington and Rideout,
2018; Rice et al., 2019)), are involved in the caste diﬀerentiation in
eusocial insects (Marshall et al., 2009; Trible and Kronauer, 2017;
McAfee et al., 2019). This suggests that the gene regulatory networks
that orchestrate variation among the physical castes in the eusocial
insect colony may be as extensive as those underlying sexual di-
morphism in solitary insects, potentially even reusing many of the same
molecular components (Warner et al., 2019a; Sato and Yamamoto,
2019).
5. Tinkering with the toolkit may not be enough
The Reproductive Groundplan Hypothesis (Johnson and Linksvayer,
2010; Chandra et al., 2018; Pamminger and Hughes, 2017) (& other
Toolkit-like hypotheses (Toth and Rehan, 2017)) posits that the plastic
reproductive physiology underlying life history transitions in the soli-
tary ancestors of social insects (e.g., between foraging and reproductive
stages) is also used in social insect lineages to produce distinct worker-
and queen- physiological states from the same genome (Friedman and
Gordon, 2016; Favreau et al., 2018; Reinberg, 2017). This is a simple
and potentially very powerful mechanism that allows for the evolution
of colony phenotypes (i.e. social anatomy) without the complex
genomic rewriting we emphasize in the present paper. We thus brieﬂy
explain why we think this idea is certainly true to some degree, but
insuﬃcient as a general and complete explanation for the evolution of
increasingly
complex
social
behavior
leading
to
superorganisms
(Johnson and Linksvayer, 2010; Warner et al., 2019a; Linksvayer and
Johnson, 2019).
Simple modiﬁcations to the plastic state previously associated with
reproductive life cycles may still be observed in queen-worker diﬀer-
ences observed in some species considered to be “facultatively social”.
However, in obligately eusocial insects, particularly the so-called “ad-
vanced” social insects, millions of years of evolution have shaped
colony function such that tissue- and caste-speciﬁc specialization no
longer exists within the bounds of any plausible ancestral phenotypic
plasticity. In extant eusocial taxa, we observe behavioral and physio-
logical extremes that are far beyond the range of any solitary species
(e.g. 30+ year queen life in Pogonomyrmex, agriculture & discrete
morphological castes of Atta, developmental scaling of Pheidole,
workers without ovaries in Monomorium and Brachyponera (Gotoh and
Ito, 2008), etc.). These extreme states are facilitated by strong altera-
tions to the hormonal pathways involved in generating these pheno-
types relative to the pre-eusocial ancestor or contemporary solitary
insects, as well as the usage of conserved and novel social physiological
processes used in novel contexts (Amdam and Page, 2005; Dolezal
et al., 2012; LeBoeuf et al., 2018; Rodrigues and Flatt, 2016; Negroni
et al., 2019). That is, while many conserved molecular mechanisms
involved in basic insect reproductive physiology are certainly involved
in generating both variation in reproductive and non-reproductive
stages in the life cycle of solitary insects as well as variation in social
insect reproductive physiology between queens and workers, the evo-
lution of queen-worker dimorphism, and more broadly the evolution of
colony-level social anatomy and social physiology truly involve phe-
notypic innovation, and not only simple modiﬁcation of the expression
of highly conserved insect “groundplans” or “toolkits” (Johnson and
Linksvayer, 2010; Warner et al., 2019a).
6. Case studies in colony physiology: ancestral traits under colony
control, and novel colony traits
There are broadly two kinds of phenotypes (measurable traits or
characteristics) of eusocial insects. First there are phenotypes that can
be measured from a single nestmate body, such as head width or
ovariole number. Second, there are traits that are the outcomes of
collective behavior and cannot be measured in single nestmates, for
example, nest architecture or rate of brood production. Traits of the
ﬁrst kind, which manifest as variation in nestmate morphology or gene
expression, bear direct homology to traits of solitary insects (Lemanski
et al., 2019; Jandt et al., 2014). However, in eusocial insects, these
bodily traits have fallen under extensive control of other nestmates via
social physiology, so that even though these traits can be measured on a
single nestmate, the traits are inﬂuenced by the physiological state of
the colony during development, and properties of other group members
as well (Linksvayer, 2015; Johnson and Linksvayer, 2010; Linksvayer,
2006; Linksvayer and Wade, 2016). The second kind of traits are not
simply modiﬁcations of insect body physiology, as they reﬂect colony-
speciﬁc traits that arise only in the context of group living, such as
brood ratio or degree of reproductive skew. Additional examples of
colony-level traits include variation in social immunity, royal jelly
production, behavior, or nest architecture. These truly collective traits
D.A. Friedman, et al.
Hormones and Behavior 122 (2020) 104757
4

## Page 5

arise from the interaction of nestmates and the environment, and un-
surprisingly the mechanisms that regulate these colony traits are likely
largely unconnected or functionally absent in solitary insects.
7. Colony-level physiological regulation of worker and queen
traits
Here we cover several case studies that reﬂect the broad range of
physiological elaborations we see in eusocial insects, highlighting ex-
amples where physiological and functional genomic studies have elu-
cidated mechanistic details about colony traits. Regulation of female
fertility and reproduction is the crux of the eusocial colony lifestyle.
Within a eusocial insect colony, the reproductive skew between queens
(who can lay thousands of eggs in some species) and workers (who
usually do not lay eggs, and may lack ovaries entirely) can be extreme.
These diﬀerences in fertility are linked to morphological, hormonal,
and transcriptomic diﬀerences in essentially every tissue of the body
(Warner et al., 2019a). Diverse social mechanisms regulate the devel-
opment and maintenance of these diﬀerences, including short-range
molecular signaling (Trawinski and Fahrbach, 2018), control of nutri-
tional intake (Vaiserman, 2014), and multiple modes of physical in-
teraction such as piping in honey bees and drumming in paper wasps
(Jeanne and Suryanarayanan, 2011; Schlegel et al., 2012; Tibbetts
et al., 2018). In various ant and bee species, secretions passed among
workers and queens can inﬂuence the fertility of all engaged actors, and
thus inﬂuence colony productivity overall. In pharaoh ants and ﬁre
ants, queen fecundity is strongly aﬀected by the presence of larvae, as
well as the secretions made by larvae of speciﬁc stages (Tschinkel,
1995; Warner et al., 2016). Honey bee queens are stimulated to produce
more eggs by being exposed to brood pheromone (Sagili and Pankiw,
2009), a positive feedback cycle within the colony where egg-laying
stimulates more egg-laying. Another primary regulator of fertility in
honey bees is queen mandibular pheromone (QMP). QMP is produced
by active queens and has the eﬀect of suppressing fertility and inducing
other physiological changes in nearby workers, thus it is a negative
feedback signal. The genes with expression responsive to queen pher-
omones are partially conserved among Lasius ants and Apis and Bombus
bees despite vast evolutionary and ecological diﬀerences among these
species (Holman et al., 2019). Interestingly, pharmacological treatment
of Drosophila fruit ﬂies with honey bee QMP seems to exert a similar
phenotypic eﬀect as in bees (e.g. repression of fertility in females), and
also triggers behavioral changes in males (Croft et al., 2017). This is
consistent with the notion that distribution of colony physiological may
arise through the reuse of pheromonal mechanisms that are present in
solitary insects, acting through novel use of inputs and outputs that
have conserved for long evolutionary periods. A general caveat of
pharmacological or genetic loss/gain-of-function experiments is that
drastic changes to a hormone signaling axis may induce organismal or
colony outcomes that do not reﬂect the natural physiological role of the
hormone.
8. Hypotheses for social physiology
Here we present hypotheses regarding the evolutionary and func-
tional genomics of behavior in eusocial insects. These hypotheses set a
course for the integrated understanding of colony function as arising
from nestmate specialization and coordination processes that have been
shaped by colony-level selection. We stress that all hypotheses should
be evaluated empirically using rigorous phylogenetic comparative
methodology to disentangle the relative importance of genomic, eco-
logical, and behavioral constraints, while explicitly accounting for
evolutionary history (Kamhi et al., 2017; Blanchard and Moreau, 2017;
Nelsen et al., 2018; Field and Toyoizumi, 2020).
9. Hypotheses for glands
We hypothesize that the distributed nature of the colony-level
physiology of eusocial insect species means that the cumulative number
of exocrine glands in all classes of nestmates in eusocial species will be
larger when compared to solitary insects, and also that social insect
glands will have more complex or voluminous glandular secretions. The
increased repertoire of exocrine glands and complexity of exocrine
glandular secretions likely evolves via duplication and neofunctionali-
zation or subfunctionalization of conserved glands and underlying
genes. Further, there may be patterns within eusocial taxa such that
species with higher social complexity may have more specialized
glandular structure present across nestmates. From an evolutionary
signaling theory perspective, once a nestmate exocrine gland has be-
come fully co-opted into colony-level regulatory networks, its dynamics
and constraints will approximate that of organismal endocrine glands.
Thus we hypothesize that molecular stimuli shared among nestmates
have been selected for high-ﬁdelity and rapid coordination of colony
physiology to changing demands. We hypothesize that eusociality
provides a new context for honest signaling systems to become elabo-
rated such that the nature of the molecular signaling among nestmates
can be more complex than social cues in non-eusocial species
(Leonhardt et al., 2016). We hypothesize that the transfer of direct
mediators of insect physiology among nestmates (microRNAs or chro-
matin remodelers in Apis royal jelly (Kurth et al., 2019), hormones in
nurse feeding ﬂuid (LeBoeuf et al., 2016)) will not induce antagonistic
responses observed in solitary insects (such as sex conﬂict in Drosophila
(Miller and Pitnick, 2002)), even when some of the same molecules may
be used. We also hypothesize that recent ﬁndings in some eusocial
species, such as carpenter ants, showing direct transfer of hormones via
trophallaxis, will be found to be commonplace in eusocial clades
(LeBoeuf et al., 2016; LeBoeuf et al., 2018).
10. Hypotheses for signaling pathways
We hypothesize that elaboration and partitioning of ancestral sig-
nals will occur such that receptors, signaling pathways, and metabolic
pathways that were expressed over the course of the lifespan of the
solitary ancestor, will be expressed synchronously, but distinctly by
various castes, in the eusocial colony. The exocrine glands and che-
mosensory organs, (McKenzie et al., 2014; Hojo et al., 2015) in parti-
cular, can be expected to have strongly partitioned expression among
castes and tasks (McKenzie et al., 2014; Hojo et al., 2015). One chal-
lenge for transcriptomic and epigenomic studies of brain function is
that the brain undergoes many types of physiological changes for which
gene expression changes are delayed, complex, or absent (e.g. topolo-
gical changes in neural circuits, protein modiﬁcation at synapses, time
lags between neural transcription and translation). This can be con-
trasted with exocrine glands, for which the transcriptome can be ex-
pected to more closely approximate the instantaneous secretory func-
tion of the tissue due to rapid transcriptomic turnover (Jasper et al.,
2015; Feyertag et al., 2017). We expect that neurotranscriptomic ap-
proaches involving single-cell proﬁling of eusocial insect brain tissue
along with live-imaging and reverse genetic approaches will be re-
quired to reach nuanced understanding about the neurophysiology of
nestmate behavior (Yan et al., 2014; Kohno and Kubo, 2019). Notably,
collective behavior and other colony-level processes arise through in-
teractions among nestmates, so that a second layer of organization
above neurobiological mechanisms is fundamentally involved, though
research on non-eusocial insects is still relevant (Gordon, 2016b;
Feinerman and Korman, 2017; Dornhaus and Franks, 2008). Consistent
with this decentralization of cognition across multiple nestmate bodies,
colonies with increased size and specialization may have workers with
proportionally smaller brains; however the strength of this trend is
unclear (Gronenberg, 2008; Godfrey and Gronenberg, 2019). Another
implication of increased physiological specialization in colonies is that
D.A. Friedman, et al.
Hormones and Behavior 122 (2020) 104757
5

## Page 6

genes with task- and tissue-speciﬁc expression patterns may be asso-
ciated with non-linear changes in colony collective behavior, for ex-
ample by altering worker response thresholds or sensitivity to interac-
tions or ambient conditions (Muscedere et al., 2012; Friedman et al.,
2018; Wu et al., 2019).
11. Hypotheses for functional genomics and gene regulatory
networks
Gene regulatory networks of organismal colonies may be more
complex than those controlling solitary insect physiology and behavior
(Linksvayer, 2015; Johnson and Linksvayer, 2010; Warner et al.,
2019b). Here we mean that eusocial regulatory networks are more
complex in the sense that they allow for a broader range of functional
connections among genes (through interactions among nestmates), in-
creased spatial partitioning of expression (e.g. novel sex-, caste-, and
tissue-speciﬁc expression patterns), and novel expression patterns
through developmental time (e.g. age polyethism). Additionally, these
eusocial regulatory networks can be considered more complex in that
they allow the colony to exhibit emergent behaviors that are more
developed or more eﬃcient in large colonies as compared to smaller
colonies or solitary insects. Several functional genomic studies have
supported the hypothesis that eusocial species have increased reg-
ulatory complexity, reﬂected by unique patterns of transcription fac-
tors, cis-regulatory elements, and epigenetic regulatory mechanisms
(Ma et al., 2019; Simola et al., 2013; Johnson and Jasper, 2016). This
increased regulatory complexity of eusocial species may reﬂect the fact
that a single genome sequence can give rise to divergent nestmate
phenotypes via epigenetic plasticity. Coexpression network approaches
to analyzing gene expression data have been used in many functional
genomic studies of eusocial insects, in addition to the use of traditional
diﬀerential expression statistics (Mikheyev and Linksvayer, 2015;
Friedman et al., 2018; Morandin et al., 2019). Coexpression networks
consist of genes that are co-regulated across tissues, nestmates, or co-
lonies, thus potentially capturing sets of loci that are functionally linked
over developmental (Walsh et al., 2018; Mikheyev and Linksvayer,
2015) and evolutionary timescales (Morandin et al., 2017; Qiu et al.,
2018). Further research could explore how various mechanisms such as
noncoding DNA (Simola et al., 2013; Rubin et al., 2019), small RNAs
(Yan et al., 2014; Glastad et al., 2019), gene family evolution (Fontana
et al., 2020; Brand et al., 2020), and mobile element activity (Koonin,
2016; Sanllorente et al., 2020) might contribute to these patterns. Key
questions about the evolution of gene expression networks in the eu-
social insects also include how ecological factors interact with ancestral
gene regulatory network constraints in order to facilitate the transition
to eusociality (Rubenstein et al., 2019; Linksvayer and Johnson, 2019;
West-Eberhard et al., 2003), and in which ways these transitions toward
eusociality are unique versus universal (Linksvayer and Johnson, 2019;
Arsenault et al., 2019; Wright et al., 2019).
Eusocial insect regulatory networks can integrate new players over
evolutionary time, especially in novel tissues and in positions periph-
eral to gene regulatory networks (Jasper et al., 2015). These new
players in gene regulatory networks can arise via duplication followed
by neo-functionalization, or via origination of novel coding sequences
from non-coding sequences. In either case, these taxonomically-re-
stricted genes could play a crucial role in establishing and cementing
patterns of nestmate variation in physiology and behavior, for example,
by allowing task-speciﬁc evolution of coding sequences in a task-biased
paralog pair, as seen in the case of insulin (Chandra et al., 2018) and
vitellogenin (Kohlmeier et al., 2018) signaling pathways. In mammals,
it has been proposed that brain pathways can arise via duplication and
subspecialization, and thus elaborate over evolutionary time analo-
gously to gene duplication (Chakraborty and Jarvis, 2015). It would be
interesting to consider whether exocrine glands in social insects may
also
undergo
duplication
and
neofunctionalization
or
sub-
functionalization over evolutionary time, potentially facilitated by
expansions in families of transcription factors and enzymes involved in
the production of gland secretions.
We hypothesize that novel gene regulatory networks will be formed
from this decoupling of otherwise conserved pathways and traits. This
is because the colony context allows for regulatory links to arise among
nestmates in diﬀerent developmental stages (e.g. signaling between
larvae to adults (Warner et al., 2019b)), as well as utilizing physiolo-
gical regulatory connections involving tactile and vibratory mechan-
isms (Razin et al., 2013; Hager et al., 2017). This means that there is the
potential for diversiﬁed types of signaling and response in the eusocial
insect colony, as well as elaboration of the molecular mechanisms un-
derlying the response to stimuli. Functional genomic approaches that
simultaneously consider multiple interacting nestmates, e.g., based on
sequencing a time series of interacting nurse workers and larvae
(Warner et al., 2019b), can begin to disentangle the molecular me-
chanisms of social signaling and the downstream physiological and
developmental response. Exocrine gland and endocrine glands that are
linked within the same physiological pathway in a colony (e.g. reg-
ulating foraging or reproduction) are unlikely to be functional in the
same network in solitary insects, and this should be explicitly con-
sidered when performing pathway analysis or using other functional
genomic approaches. Further, work on signaling pathways related to JH
and Vitellogenin show that even the most fundamentally important
conserved genes have diﬀerent expression patterns in eusocial insects as
compared to solitary insects, as well as expression variation between
related eusocial species and among nestmates (LeBoeuf et al., 2018;
Rodrigues and Flatt, 2016; Mello et al., 2019; Trumbo, 2018; Trumbo,
2019). The convention has been to act as if use of an ortholog con-
stitutes conservation, but already for key cases such as PKG we know
the same locus can be associated with a trait (e.g. “playing a conserved
role”) yet still have unpredictable patterns of expression or functional
roles.
Holistic (i.e. colony-level) consideration of these issues is necessary
to understand how selection acts to shape gene regulatory networks
that play out across multiple insect bodies (Linksvayer, 2015). For ex-
ample, a recent study in honey bees found that decades of artiﬁcial
selection for increased royal jelly production was accommodated by
changes in the expression of chemoreceptor proteins in nurse antenna
(Wu et al., 2019). This can be understood from the perspective that
nurse antennae are one of the multiple tissues that are involved in the
emergent regulation of colony reproductive investment and royal jelly
production. In other words, colonies may respond to evolutionary and
ecological challenges in a non-linear fashion, via shaping the expression
of genes that inﬂuence tissue-speciﬁc physiology of sensory organs and
central processing in the brain (Lemanski et al., 2019; Kocher et al.,
2018).
12. Future directions & questions
There are many opportunities for functional genomics to use eu-
social insects as model systems to address general questions about
hormones, development, and behavior. First, the epigenetic plasticity of
eusocial workers situates them as tractable models to disentangle ge-
netic and environmental inﬂuences on behavior (Yan et al., 2014;
Chittka et al., 2012). The ecological diversity of the eusocial insects
provides broad possible scope for understanding how colonies solve
niche-speciﬁc challenges, particularly since many species can be kept in
the laboratory so that genetic and environmental factors can be con-
trolled. Second, new techniques can be integrated in eusocial insect
taxa to bring about multidisciplinary synthesis. Recent and ongoing
studies are combining natural history, automated behavioral analysis,
DNA/RNA-sequencing, transgenic techniques, and pharmacological
manipulations (Friedman and Gordon, 2016; Favreau et al., 2018;
Kohno and Kubo, 2019; Arsenault et al., 2019; Friedman et al., 2017).
A key question is: How dramatic are the molecular changes neces-
sary for the major transitions to eusocial colonial living from a solitary
D.A. Friedman, et al.
Hormones and Behavior 122 (2020) 104757
6

## Page 7

or social state? How are the initial steps toward eusocial colony living
similar or diﬀerent to later stages involving the expansion of colony size
and elaboration of queen-worker dimorphism? Several previous authors
have stressed that few molecular changes may be necessary for the
initial transitions from solitary insects to small eusocial colonies
(Michener, 1969; Linksvayer and Wade, 2005). We emphasize that in
lineages with large and complex eusocial colonies, extreme molecular
changes have likely occurred that obscure the traces of initial molecular
inroads toward colony living (Warner et al., 2019a; Woodard et al.,
2011). Thus, it is important to consider to what extent the multiple
independent origins of eusociality converged on similar mechanisms
versus how often they arrived at taxa-speciﬁc patterns (Linksvayer and
Johnson, 2019).
New tools allow us to do many things in non-model systems that
previously could only be done in model systems, and systems like
Drosophila have proven helpful in broad strokes for elucidating insect
physiological processes. However, millions of years of selection for
colony function in eusocial insects means that even for conserved or-
thologs (e.g. PKG, biogenic amine receptors), gene functions may diﬀer.
This is a signiﬁcant issue for Gene Ontology (GO) based analysis of
functional genomic experiments in eusocial insects, as most GO terms in
these species are directly transferred from Drosophila. Any analysis of
eusocial insects that is templated oﬀof a (distantly related) solitary
insect species will systematically ignore the role of taxonomically re-
stricted genes (Warner et al., 2019a), overstate the role of orthologous
genes, and be unable to consider the implications of decentralized
colony physiological processes. The challenges of colony living in eu-
social insects have been accommodated through multiple types of
genomic and epigenomic changes, and research should highlight these
taxa-speciﬁc adaptations, not average over them. If the goal is to gain
unbiased insight into the genetic changes that are most biologically
important – as opposed to exploring just those genetic changes that
involve highly conserved genes with more-or-less well-characterized
functions in solitary organisms – then alternate approaches may be
required. For example, analyzing genes that seem biologically im-
portant in eusocial insects, independent of whether they are found in
other insect lineages.
Promising experimental approaches in the social insects could use
RNA-Seq, proteomics, and metabolomics on the same tissue-speciﬁc
samples across the classes of nestmates (e.g., developing larvae, adult
nurses (Warner et al., 2019b)) involved in colony physiological pro-
cesses. It is especially interesting to combine these functional genomic
analyses with computational methods such as the automated tracking of
behavior from video data (Davidson et al., 2016; Arsenault et al., 2019;
Walsh et al., 2019). For example worker-level tracking can assess how
worker heterogeneity leads to colony foraging performance (Beverly
et al., 2009; Campos et al., 2016), or how trophallaxis networks provide
robustness to variability in colony resource intake (Bles et al., 2018).
Speciﬁcally, these types of studies in eusocial insect species could
connect
multilevel-network
perspectives
on
animal
behavior
(Pasquaretta and Jeanson, 2018; Finn et al., 2019) with the molecular
mechanisms of behavioral epigenetics and neurophysiology (Friedman
and Gordon, 2016; Lemanski et al., 2019; Reinberg, 2017), in the
context of a group of species with diverse ecologies and rich natural
history.
Animal welfare statement
No animals were used in our research for this paper.
Funding
TAL was funded by National Science Foundation grant I0S-
1452520. BRJ was funded by USDA Hatch grant (CA-D-ENM 2161-H).
Declaration of competing interest
None.
References
Abouheif, E., et al., 2014. Eco-evo-devo: the time has come. Adv. Exp. Med. Biol. 781,
107–125.
Alaux, C., Maisonnasse, A., Le Conte, Y., 2010. Pheromones in a superorganism: from
gene to social regulation. Vitam. Horm. 83, 401–423.
Almond, E.J., Huggins, T.J., Crowther, L.P., Parker, J.D., Bourke, A.F.G., 2019. Queen
longevity and fecundity aﬀect conﬂict with workers over resource inheritance in a
social insect. Am. Nat. 193, 256–266.
Amdam, G. V. & Page, R. E., Jr. Intergenerational transfers may have decoupled phy-
siological and chronological age in a eusocial insect. Ageing Res. Rev. 4, 398–408
(2005).
Anderson, C., Ratnieks, F.L.W., 1999. Task partitioning in insect societies. I. Eﬀect of
colony size on queueing delay and colony ergonomic eﬃciency. Am. Nat. 154,
521–535.
Anreiter, I., Sokolowski, M.B., 2019. The foraging gene and its behavioral eﬀects:
pleiotropy and plasticity. Annu. Rev. Genet. https://doi.org/10.1146/annurev-genet-
112618-043536.
Anreiter, I., Kramer, J.M., Sokolowski, M.B., 2017. Epigenetic mechanisms modulate
diﬀerences in Drosophila foraging behavior. Proc. Natl. Acad. Sci. U. S. A. 114,
12518–12523.
Arsenault, S.V., Glastad, K.M., Hunt, B.G., 2019. Leveraging technological innovations to
investigate evolutionary transitions to eusociality. Curr Opin Insect Sci 34, 27–32.
Aylward, F.O., Currie, C.R., Suen, G., 2012. The evolutionary innovation of nutritional
symbioses in leaf-cutter ants. Insects 3, 41–61.
Beani, L., Dessì-Fulgheri, F., Cappa, F., Toth, A., 2014. The trap of sex in social insects:
from the female to the male perspective. Neurosci. Biobehav. Rev. 46 (Pt 4),
519–533.
Beverly, B.D., McLendon, H., Nacu, S., Holmes, S., Gordon, D.M., 2009. How site ﬁdelity
leads to individual diﬀerences in the foraging activity of harvester ants. Behav. Ecol.
20, 633–638.
Billen, J., 1991. Ultrastructural organization of the exocrine glands in ants. Ethol. Ecol.
Evol. 3, 67–73.
Birch, J., Okasha, S., 2015. Kin selection and its critics. Bioscience 65, 22–32.
Blanchard, B.D., Moreau, C.S., 2017. Defensive traits exhibit an evolutionary trade-oﬀ
and drive diversiﬁcation in ants. Evolution 71, 315–328.
Bles, O., Deneubourg, J.-L., Nicolis, S.C., 2018. Food dissemination in ants: robustness of
the trophallactic network against resource quality. J. Exp. Biol. 221.
Bortolotti, L., Costa, C., 2014. Chemical communication in the honey bee society. In:
Mucignat-Caretta, C. (Ed.), Neurobiology of Chemical Communication. CRC Press/
Taylor & Francis.
Brand, P., et al., 2020. The evolution of sexual signaling is linked to odorant receptor
tuning in perfume-collecting orchid bees. Nat. Commun. 11, 244.
Burgess, S.C., et al., 2017. Metabolic scaling in modular animals. Invertebr. Biol. 136,
456–472.
Campos, D., Bartumeus, F., Méndez, V., Andrade Jr., J.S., Espadaler, X., 2016. Variability
in individual activity bursts improves ant foraging success. J. R. Soc. Interface 13,
20160856.
Canciani, M., Arnellos, A., Moreno, A., 2019. Revising the superorganism: an organiza-
tional approach to complex eusociality. Front. Psychol. 10 (2653).
Cerdá, X., van Oudenhove, L., Bernstein, C., Boulay, R.R., 2014. A list of and some
comments about the trail pheromones of ants. Nat. Prod. Commun. 9, 1115–1122.
Chakraborty, M., Jarvis, E.D., 2015. Brain evolution by brain pathway duplication.
Philos. Trans. R. Soc. Lond. Ser. B Biol. Sci. 370, 20150056.
Chandra, V., et al., 2018. Social regulation of insulin signaling and the evolution of eu-
sociality in ants. Science 361, 398–402.
Chittka, A., Wurm, Y., Chittka, L., 2012. Epigenetics: the making of ant castes. Current
biology: CB 22, R835–R838.
Colgren, J., Nichols, S.A., 2019. The signiﬁcance of sponges for comparative studies of
developmental evolution. Wiley Interdiscip. Rev. Dev. Biol. e359.
Cooper, G.A., West, S.A., 2018. Division of labour and the evolution of extreme specia-
lization. Nat Ecol Evol 2, 1161–1167.
Croft, J.R., Liu, T., Camiletti, A.L., Simon, A.F., Thompson, G.J., 2017. Sexual response of
male Drosophila to honey bee queen mandibular pheromone: implications for genetic
studies of social insects. J. Comp. Physiol. A Neuroethol. Sens. Neural Behav. Physiol.
203, 143–149.
Davidson, J.D., Arauco-Aliaga, R.P., Crow, S., Gordon, D.M., Goldman, M.S., 2016. Eﬀect
of interactions between harvester ants on forager decisions. Front. Ecol. Evol. 4 (115).
d’Ettorre, P., 2016. Genomic and brain expansion provide ants with reﬁned sense of smell.
Proc. Natl. Acad. Sci. U. S. A. 113, 13947–13949.
Dolezal, A.G., Brent, C.S., Hölldobler, B., Amdam, G.V., 2012. Worker division of labor
and endocrine physiology are associated in the harvester ant, Pogonomyrmex cali-
fornicus. J. Exp. Biol. 215, 454–460.
Dornhaus, A., Franks, N.R., 2008. Individual and collective cognition in ants and other
insects (Hymenoptera: Formicidae). Myrmecol. News 11.
Durand, P.M., Barreto Filho, M.M., Michod, R.E., 2019. Cell death in evolutionary tran-
sitions in individuality. Yale J. Biol. Med. 92, 651–662.
Eksi, S.E., Barmina, O., McCallough, C.L., Kopp, A., Orenic, T.V., 2018. A Distalless-re-
sponsive enhancer of the Hox gene sex combs reduced is required for segment- and
sex-speciﬁc sensory organ development in Drosophila. PLoS Genet. 14, e1007320.
D.A. Friedman, et al.
Hormones and Behavior 122 (2020) 104757
7

## Page 8

Favreau, E., Martínez-Ruiz, C., Rodrigues Santiago, L., Hammond, R.L., Wurm, Y., 2018.
Genes and genomic processes underpinning the social lives of ants. Curr Opin Insect
Sci 25, 83–90.
Feinerman, O., Korman, A., 2017. Individual versus collective cognition in social insects.
J. Exp. Biol. 220, 73–82.
Feyertag, F., Berninsone, P.M., Alvarez-Ponce, D., 2017. Secreted proteins defy the ex-
pression level-evolutionary rate anticorrelation. Mol. Biol. Evol. 34, 692–706.
Field, J., Toyoizumi, H., 2020. The evolution of eusociality: no risk-return tradeoﬀbut the
ecology matters. Ecol. Lett. 23, 518–526.
Fielde, A.M., Parker, G.H., 1904. The reactions of ants to material vibrations. Proc. Acad.
Natl. Sci. Phila. 56, 642–650.
Finn, K.R., Silk, M.J., Porter, M.A., Pinter-Wollman, N., 2019. The use of multilayer
network analysis in animal behaviour. Anim. Behav. 149, 7–22.
Fontana, S., et al., 2020. The ﬁre ant social supergene is characterized by extensive gene
and transposable element copy number variation. Mol. Ecol. 29, 105–120.
Friedman, D.A., Gordon, D.M., 2016. Ant genetics: reproductive physiology, worker
morphology, and behavior. Annu. Rev. Neurosci. 39, 41–56.
Friedman, D.A., Gordon, D.M., Luo, L., 2017. The MutAnts are here. Cell 170, 601–602.
Friedman, D.A., et al., 2018. The role of dopamine in the collective regulation of foraging
in harvester ants. iScience 8, 283–294.
Gilbert, S.F., Sapp, J., Tauber, A.I., 2012. A symbiotic view of life: we have never been
individuals. Q. Rev. Biol. 87, 325–341.
Gillooly, J.F., Hou, C., Kaspari, M., 2010. Eusocial insects as superorganisms: insights
from metabolic theory. Commun. Integr. Biol. 3, 360–362.
Glastad, K.M., Hunt, B.G., Goodisman, M.A.D., 2019. Epigenetics in insects: genome
regulation and the generation of phenotypic diversity. Annu. Rev. Entomol. 64,
185–203.
Godfrey, R.K., Gronenberg, W., 2019. Brain evolution in social insects: advocating for the
comparative approach. J. Comp. Physiol. A Neuroethol. Sens. Neural Behav. Physiol.
205, 13–32.
Goldsby, H.J., Knoester, D.B., Ofria, C., Kerr, B., 2014. The evolutionary origin of somatic
cells under the dirty work hypothesis. PLoS Biol. 12, e1001858.
Gordon, D.M., 1989. Dynamics of task switching in harvester ants. Anim. Behav. 38,
194–204.
Gordon, D.M., 2013. The rewards of restraint in the collective regulation of foraging by
harvester ant colonies. Nature 498, 91–93.
Gordon, D.M., 2016a. From division of labor to the collective behavior of social insects.
Behav. Ecol. Sociobiol. 70, 1101–1108.
Gordon, D.M., 2016b. The evolution of the algorithms for collective behavior. Cell Syst 3,
514–520.
Gordon, D.M., Dektar, K.N., Pinter-Wollman, N., 2013. Harvester ant colony variation in
foraging activity and response to humidity. PLoS One 8, e63363.
Gospocic, J., et al., 2017. The neuropeptide corazonin controls social behavior and caste
identity in ants. Cell 170, 748–759 e12.
Gotoh, A., Ito, F., 2008. Seasonal cycle of colony structure in the Ponerine ant
Pachycondyla chinensis in western Japan (Hymenoptera, Formicidae). Insect. Soc.
55, 98–104.
Gronenberg, W., 2008. Structure and function of ant (Hymenoptera: Formicidae) brains:
strength in numbers. Myrmecol. News 11, 25–36.
Hager, F.A., Kirchner, L., Kirchner, W.H., 2017. Directional vibration sensing in the
leafcutter ant Atta sexdens. Biol. Open 6, 1949–1952.
Heylen, K., et al., 2008. Amfor expression in the honeybee brain: a trigger mechanism for
nurse-forager transition. J. Insect Physiol. 54, 1400–1403.
Hojo, M.K., et al., 2015. Antennal RNA-sequencing analysis reveals evolutionary aspects
of chemosensory proteins in the carpenter ant, Camponotus japonicus. Sci. Rep. 5,
13541.
Hölldobler, B., Wilson, E.O., 2009. The Superorganism: The Beauty, Elegance, and
Strangeness of Insect Societies. W. W. Norton & Company.
Hölldobler, B., Obermayer, M., Plowes, N.J.R., Fisher, B.L., 2014. New exocrine glands in
ants: the hypostomal gland and basitarsal gland in the genus Melissotarsus
(Hymenoptera: Formicidae). Naturwissenschaften 101, 527–532.
Holman, L., 2012. Costs and constraints conspire to produce honest signaling: insights
from an ant queen pheromone. Evolution 66, 2094–2105.
Holman, L., Linksvayer, T.A., d’Ettorre, P., 2013. Genetic constraints on dishonesty and
caste dimorphism in an ant. Am. Nat. 181, 161–170.
Holman, L., Helanterä, H., Trontti, K., Mikheyev, A.S., 2019. Comparative transcriptomics
of social insect queen pheromones. Nat. Commun. 10, 1593.
Ingram, K.K., Kleeman, L., Peteru, S., 2011. Diﬀerential regulation of the foraging gene
associated with task behaviors in harvester ants. BMC Ecol. 11, 19.
Ingram, K.K., et al., 2016. Context-dependent expression of the foraging gene in ﬁeld
colonies of ants: the interacting roles of age, environment and task. Proc. Biol. Sci.
283, 20160841.
Invernizzi, E., Ruxton, G.D., 2019. Deconstructing collective building in social insects:
implications for ecological adaptation and evolution. Insect. Soc. 66, 507–518.
Jandt, J.M., et al., 2014. Behavioural syndromes and social insects: personality at mul-
tiple levels. Biol. Rev. Camb. Philos. Soc. 89, 48–67.
Jasper, W.C., et al., 2015. Large-scale coding sequence change underlies the evolution of
postdevelopmental novelty in honey bees. Mol. Biol. Evol. 32, 334–346.
Jeanne, R.L., 2016. Division of labor is not a process or a misleading concept. Behav. Ecol.
Sociobiol. 70, 1109–1112.
Jeanne, R.L., Suryanarayanan, S., 2011. A new model for caste development in social
wasps. Commun. Integr. Biol. 4, 373–377.
Johnson, B.R., 2010. Division of labor in honeybees: form, function, and proximate me-
chanisms. Behav. Ecol. Sociobiol. 64, 305–316.
Johnson, B.R., Jasper, W.C., 2016. Complex patterns of diﬀerential expression in candi-
date master regulatory genes for social behavior in honey bees. Behav. Ecol.
Sociobiol. 70, 1033–1043.
Johnson, B.R., Linksvayer, T.A., 2010. Deconstructing the superorganism: social phy-
siology, groundplans, and sociogenomics. Q. Rev. Biol. 85, 57–79.
Kamhi, J.F., Arganda, S., Moreau, C.S., Traniello, J.F.A., 2017. Origins of aminergic
regulation of behavior in complex insect social systems. Front. Syst. Neurosci.
11 (74).
Katzav-Gozansky, T., Soroker, Victoria, Ibarra, F., Francke, W., Hefetz, A., 2001. Dufour’s
gland secretion of the queen honeybee (Apis mellifera): an egg discriminator pher-
omone or a queen signal? Behav. Ecol. Sociobiol. 51, 76–86.
Kaun, K.R., Sokolowski, M.B., 2009. cGMP-dependent protein kinase: linking foraging to
energy homeostasis. Genome 52, 1–7.
Khoury, D.S., Barron, A.B., Myerscough, M.R., 2013. Modelling food and population
dynamics in honey bee colonies. PLoS One 8, e59084.
Kocher, S.D., et al., 2018. The genetic basis of a social polymorphism in halictid bees. Nat.
Commun. 9, 4338.
Kohlmeier, P., Feldmeyer, B., Foitzik, S., 2018. Vitellogenin-like A–associated shifts in
social cue responsiveness regulate behavioral task specialization in an ant. PLoS Biol.
16, e2005747.
Kohno, H., Kubo, T., 2019. Genetics in the honey bee: achievements and prospects toward
the functional analysis of molecular and neural mechanisms underlying social be-
haviors. Insects 10.
Koonin, E.V., 2016. Viruses and mobile elements as drivers of evolutionary transitions.
Philos. Trans. R. Soc. Lond. Ser. B Biol. Sci. 371.
Korb, J., 2016. Towards a more pluralistic view of termite social evolution. Ecological
Entomology 41, 34–36.
Kurth, T., Kretschmar, S., Buttstedt, A., 2019. Royal jelly in focus. Insect. Soc. 66, 81–89.
LeBoeuf, A.C., Benton, R., Keller, L., 2013. The molecular basis of social behavior: models,
methods and advances. Curr. Opin. Neurobiol. 23, 3–10.
LeBoeuf, A.C., et al., 2016. Oral transfer of chemical cues, growth proteins and hormones
in social insects. Elife 5, e20375.
LeBoeuf, A.C., et al., 2018. Molecular evolution of juvenile hormone esterase-like proteins
in a socially exchanged ﬂuid. Sci. Rep. 8, 17830.
Lemanski, N.J., Cook, C.N., Smith, B.H., Pinter-Wollman, N., 2019. A multiscale review of
behavioral variation in collective foraging behavior in honey bees. Insects 10, 370.
Leonhardt, S.D., Menzel, F., Nehring, V., Schmitt, T., 2016. Ecology and evolution of
communication in social insects. Cell 164, 1277–1287.
Liebig, J., Peeters, C., Lldobler, B.H., 1999. Worker policing limits the number of re-
productives in a ponerine ant. Proc. R. Soc. B Biol. Sci. 266, 1865.
Linksvayer, T.A., 2006. Direct, maternal, and sibsocial genetic eﬀects on individual and
colony traits in an ant. Evolution 60, 2552–2561.
Linksvayer, T.A., 2015. Chapter eight-the molecular and evolutionary genetic implica-
tions of being truly social for the social insects. In: Zayed, A., Kent, C.F. (Eds.),
Advances in Insect Physiology. 48. Academic Press, pp. 271–292.
Linksvayer, T.A., Johnson, B.R., 2019. Re-thinking the social ladder approach for eluci-
dating the evolution and molecular basis of insect societies. Current Opinion in Insect
Science 34, 123–129.
Linksvayer, T.A., Wade, M.J., 2005. The evolutionary origin and elaboration of sociality
in the aculeate Hymenoptera: maternal eﬀects, sib-social eﬀects, and heterochrony.
Q. Rev. Biol. 80, 317–336.
Linksvayer, T.A., Wade, M.J., 2016. Theoretical predictions for sociogenomic data: the
eﬀects of kin selection and sex-limited expression on the evolution of social insect
genomes. Front. Ecol. Evol. 4, 65.
Liu, Q., Jin, L.H., 2017. Organ-to-organ communication: a Drosophila gastrointestinal
tract perspective. Front Cell Dev Biol 5 (29).
Lucas, C., Sokolowski, M.B., 2009. Molecular basis for changes in behavioral state in ant
social behaviors. Proc. Natl. Acad. Sci. U. S. A. 106, 6351–6356.
Ma, R., Rangel, J., Grozinger, C.M., 2019. Honey bee (Apis mellifera) larval pheromones
may regulate gene expression related to foraging task specialization. BMC Genomics
20, 592.
Malé, P.-J.G., et al., 2017. An ant-plant mutualism through the lens of cGMP-dependent
kinase genes. Proc. Biol. Sci. 284, 20170896.
Maori, E., et al., 2019. A transmissible RNA pathway in honey bees. Cell Rep. 27,
1949–1959 e6.
Marshall, J.A.R., et al., 2009. On optimal decision-making in brains and social insect
colonies. J. R. Soc. Interface 6, 1065–1074.
McAfee, A., Pettis, J.S., Tarpy, D.R., Foster, L.J., 2019. Feminizer and doublesex knock-
outs cause honey bees to switch sexes. PLoS Biol. 17, e3000256.
McKenzie, S.K., Oxley, P.R., Kronauer, D.J.C., 2014. Comparative genomics and tran-
scriptomics in ants provide new insights into the evolution and function of odorant
binding and chemosensory proteins. BMC Genomics 15, 718.
Mello, T.R.P., Aleixo, A.C., Pinheiro, D.G., 2019. Hormonal control and target genes of
ftz-f1 expression in the honeybee Apis mellifera: a positive loop linking juvenile
hormone, ftz-f1, and vitellogenin. Insect Mol. Biol. 1, 145–159. https://www.ncbi.
nlm.nih.gov/pubmed/30270498.
Michener, C.D., 1969. Comparative social behavior of bees. Annu. Rev. Entomol. 14,
299–342.
Mikheyev, A.S., Linksvayer, T.A., 2015. Genes associated with ant social behavior show
distinct transcriptional and evolutionary patterns. Elife 4, e04775.
Miller, G.T., Pitnick, S., 2002. Sperm-female coevolution in Drosophila. Science 298,
1230–1233.
Millington, J.W., Rideout, E.J., 2018. Sex diﬀerences in Drosophila development and
physiology. Current Opinion in Physiology 6, 46–56.
Morandin, C., Mikheyev, A.S., Pedersen, J.S., Helanterä, H., 2017. Evolutionary con-
straints shape caste-speciﬁc gene expression across 15 ant species. Evolution 71,
1273–1284.
Morandin, C., Brendel, V.P., Sundström, L., Helanterä, H., Mikheyev, A.S., 2019. Changes
D.A. Friedman, et al.
Hormones and Behavior 122 (2020) 104757
8

## Page 9

in gene DNA methylation and expression networks accompany caste specialization
and age-related physiological changes in a social insect. Mol. Ecol. 28, 1975–1993.
Muscedere, M.L., Johnson, N., Gillis, B.C., Kamhi, J.F., Traniello, J.F.A., 2012. Serotonin
modulates worker responsiveness to trail pheromone in the ant Pheidole dentata. J.
Comp. Physiol. A Neuroethol. Sens. Neural Behav. Physiol. 198, 219–227.
Musselman, L.P., Kühnlein, R.P., 2018. Drosophila as a model to study obesity and me-
tabolic disease. J. Exp. Biol. 221.
Nässel, D.R., Zandawala, M., 2019. Recent advances in neuropeptide signaling in
Drosophila, from genes to physiology and behavior. Prog. Neurobiol. https://doi.org/
10.1016/j.pneurobio.2019.02.003.
Negroni, M.A., Foitzik, S., Feldmeyer, B., 2019. Long-lived Temnothorax ant queens
switch from investment in immunity to antioxidant production with age. Sci. Rep. 9,
7270.
Nelsen, M.P., Ree, R.H., Moreau, C.S., 2018. Ant-plant interactions evolved through in-
creasing interdependence. Proc. Natl. Acad. Sci. U. S. A. 115, 12253–12258.
Neuhof, M., Levin, M., Rechavi, O., 2016. Vertically- and horizontally-transmitted
memories - the fading boundaries between regeneration and inheritance in planaria.
Biol. Open 5, 1177–1188.
Oi, C.A., et al., 2015. The origin and evolution of social insect queen pheromones: novel
hypotheses and outstanding problems. Bioessays 37, 808–821.
Okasha, S., 2016. The relation between kin and multilevel selection: an approach using
causal graphs. Br. J. Philos. Sci. 67, 435–470.
Pamminger, T., Hughes, W.O.H., 2017. Testing the reproductive groundplan hypothesis
in ants (Hymenoptera: Formicidae). Evolution 71, 153–159.
Pankiw, T., Page Jr., R.E., Kim Fondrk, M., 1998. Brood pheromone stimulates pollen
foraging in honey bees (Apis mellifera). Behav. Ecol. Sociobiol. 44, 193–198.
Pasquaretta, C., Jeanson, R., 2018. Division of labor as a bipartite network. Behav. Ecol.
29, 342–352.
Perry, C.J., Barron, A.B., 2013. Neural mechanisms of reward in insects. Annu. Rev.
Entomol. 58, 543–562.
Perry, C.J., Søvik, E., Myerscough, M.R., Barron, A.B., 2015. Rapid behavioral maturation
accelerates failure of stressed honey bee colonies. Proc. Natl. Acad. Sci. U. S. A. 112,
3427–3432.
Petersen, M., et al., 2019. Diversity and evolution of the transposable element repertoire
in arthropods with particular reference to insects. BMC Evol. Biol. 19, 11.
Qiu, B., et al., 2018. Towards reconstructing the ancestral brain gene-network regulating
caste diﬀerentiation in ants. Nat Ecol Evol 2, 1782–1791.
Quiñones, A.E., Henriques, G.J.B., Pen, I., 2020. Queen-worker conﬂict can drive the
evolution of social polymorphism and split sex ratios in facultatively eusocial life
cycles. Evolution 74, 15–28.
Ramdya, P., et al., 2015. Mechanosensory interactions drive collective behaviour in
Drosophila. Nature 519, 233–236.
Ramdya, P., Schneider, J., Levine, J.D., 2017. The neurogenetics of group behavior in
Drosophila melanogaster. J. Exp. Biol. 220, 35–41.
Ratnieks, F.L.W., Visscher, P.K., 1989. Worker policing in the honeybee. Nature 342,
796–797.
Ratnieks, F.L.W., Foster, K.R., Wenseleers, T., 2011. Darwin’s special diﬃculty: the
evolution of ‘neuter insects’ and current theory. Behav. Ecol. Sociobiol. 65, 481–492.
Razin, N., Eckmann, J.-P., Feinerman, O., 2013. Desert ants achieve reliable recruitment
across noisy interactions. J. R. Soc. Interface 10, 20130079.
Reinberg, D., 2017. Epigenetics of social insects (ants). Annu. Rev. Genet. 51.
Rice, G.R., et al., 2019. Modular tissue-speciﬁc regulation of doublesex underpins sexually
dimorphic development in Drosophila. Development 146.
Rivera, M.D., Donaldson-Matasci, M., Dornhaus, A., 2015. Quitting time: when do honey
bee foragers decide to stop foraging on natural resources? Front. Ecol. Evol. 3 (50).
Rodrigues, M.A., Flatt, T., 2016. Endocrine uncoupling of the trade-oﬀbetween re-
production and somatic maintenance in eusocial insects. Curr Opin Insect Sci 16, 1–8.
Rose, C., Mian, I.S., 2015. A fundamental framework for molecular communication
channels: timing payload. In: 2015 IEEE International Conference on
Communications (ICC), pp. 1043–1048.
Rubenstein, D.R., et al., 2019. Coevolution of genome architecture and social behavior.
Trends Ecol. Evol. 34, 844–855.
Rubin, B.E.R., Jones, B.M., Hunt, B.G., Kocher, S.D., 2019. Rate variation in the evolution
of non-coding DNA associated with social evolution in bees. Philos. Trans. R. Soc.
Lond. Ser. B Biol. Sci. 374, 20180247.
Sagili, R.R., Pankiw, T., 2009. Eﬀects of brood pheromone modulated brood rearing
behaviors on honey bee (Apis mellifera L.) Colony growth. J. Insect Behav. 22,
339–349.
Sanllorente, O., et al., 2020. Complex evolutionary history of Mboumar, a mariner ele-
ment widely represented in ant genomes. Sci. Rep. 10, 2610.
Sato, K., Yamamoto, D., 2019. The mode of action of fruitless: is it an easy matter to
switch the sex? Genes Brain Behav 19:e12606. https://onlinelibrary.wiley.com/doi/
full/10.1111/gbb.12606.
Schlegel, T., Visscher, P.K., Seeley, T.D., 2012. Beeping and piping: characterization of
two mechano-acoustic signals used by honey bees in swarming. Naturwissenschaften
99, 1067–1071.
Schultz, T.R., Brady, S.G., 2008. Major evolutionary transitions in ant agriculture. Proc.
Natl. Acad. Sci. U. S. A. 105, 5435–5440.
Seeley, T.D., 2009. The Wisdom of the Hive: Social Physiology of Honey Bee Colonies.
Harvard University Press.
Shields, E.J., Sheng, L., Weiner, A.K., Garcia, B.A., Bonasio, R., 2018. High-quality
genome assemblies reveal long non-coding RNAs expressed in ant brains. Cell Rep.
23, 3078–3090.
Signor, S.A., Liu, Y., Rebeiz, M., Kopp, A., 2016. Genetic convergence in the evolution of
male-speciﬁc color patterns in Drosophila. Curr. Biol. 26, 2423–2433.
Silberman, R.E., Gordon, D., Ingram, K.K., 2016. Nutrient stores predict task behaviors in
diverse ant species. Insect. Soc. 63, 299–307.
Simola, D.F., et al., 2013. Social insect genomes exhibit dramatic evolution in gene
composition and regulation while preserving regulatory features linked to sociality.
Genome Res. 23, 1235–1247.
Søvik, E., Perry, C.J., Barron, A.B., 2015. Chapter six-insect reward systems: comparing
ﬂies and bees. In: Zayed, A., Kent, C.F. (Eds.), Advances in Insect Physiology. 48.
Academic Press, pp. 189–226.
Stark, L., Theodoridis, G.C., 1973. Information theory in physiology. In: Engineering
Principles in Physiology, pp. 13–32. https://doi.org/10.1016/b978-0-12-136201-0.
50009-x.
Stökl, J., Steiger, S., 2017. Evolutionary origin of insect pheromones. Curr Opin Insect Sci
24, 36–42.
Struk, A.A., et al., 2019. Self-regulation and the foraging gene (PRKG1) in humans. Proc.
Natl. Acad. Sci. U. S. A. https://doi.org/10.1073/pnas.1809924116.
Sugden, A.M., 2000. A puzzling metazoan body plan. Science 289 (5477), 5217. https://
science.sciencemag.org/content/289/5477/217.3.
Szathmáry, E., 2015. Toward major evolutionary transitions theory 2.0. Proc. Natl. Acad.
Sci. U. S. A. 112, 10104–10111.
Szathmáry, E., Smith, J.M., 1995. The major evolutionary transitions. Nature 374,
227–232.
Tibbetts, E.A., Fearon, M.L., Wong, E., 2018. Rapid juvenile hormone downregulation in
subordinate wasp queens facilitates stable cooperation. of the Royal … 285,
20172645. https://royalsocietypublishing.org/doi/10.1098/rspb.2017.2645.
Toth, A.L., Rehan, S.M., 2017. Molecular evolution of insect sociality: an Eco-Evo-Devo
perspective. Annu. Rev. Entomol. 62, 419–442.
Trawinski, A.M., Fahrbach, S.E., 2018. Queen mandibular pheromone modulates hemo-
lymph ecdysteroid titers in adult Apis mellifera workers. Apidologie 49, 346–358.
https://link.springer.com/article/10.1007/s13592-018-0562-6.
Traynor, K.S., Le Conte, Y., Page, R.E., 2015. Age matters: pheromone proﬁles of larvae
diﬀerentially inﬂuence foraging behaviour in the honeybee, Apis mellifera. Anim.
Behav. 99, 1–8.
Trible, W., Kronauer, D.J.C., 2017. Caste development and evolution in ants: it’s all about
size. J. Exp. Biol. 220, 53–62.
Tripet, F., Nonacs, P., 2004. Foraging for work and age-based polyethism: the roles of age
and previous experience on task choice in ants. Ethology 110, 863–877.
Trumbo, S.T., 2018. Juvenile hormone and parental care in subsocial insects: implications
for the role of juvenile hormone in the evolution of sociality. Curr Opin Insect Sci 28,
13–18.
Trumbo, S.T., 2019. The physiology of insect families: a door to the study of social
evolution. Adv. In Insect Phys. 56, 203.
Tschinkel, W.R., 1995. Stimulation of ﬁre ant queen fecundity by a highly speciﬁc brood
stage. Ann. Entomol. Soc. Am. 88, 876–882.
Tsuruyama, T., 2018. Information thermodynamics of the cell signal transduction as a
Szilard engine. Entropy 20, 224.
Vaiserman, A., 2014. Developmental epigenetic programming of caste-speciﬁc diﬀerences
in social insects: an impact on longevity. Curr. Aging Sci. 7, 176–186.
Verhulst, E.C., van de Zande, L., 2015. Double nexus–Doublesex is the connecting element
in sex determination. Brief. Funct. Genomics 14, 396–406.
Villalta, I., Abril, S., Cerdá, X., Boulay, R., 2018. Queen control or queen signal in ants:
what remains of the controversy 25 years after Keller and Nonacs’ seminal paper? J.
Chem. Ecol. 44, 805–817.
Wagner, G.P., Zhang, J., 2011. The pleiotropic structure of the genotype–phenotype map:
the evolvability of complex organisms. Nat. Rev. Genet. 12, 204.
Waibel, M., Floreano, D., Magnenat, S., Keller, L., 2006. Division of labour and colony
eﬃciency in social insects: eﬀects of interactions between genetic architecture,
colony kin structure and rate of perturbations. Proc. Biol. Sci. 273, 1815–1823.
Wainselboim, A.J., Roces, F., Farina, W.M., 2002. Honeybees assess changes in nectar
ﬂow within a single foraging bout. Anim. Behav. 63, 1–6.
Walsh, J.T., Warner, M.R., Kase, A., Cushing, B.J., Linksvayer, T.A., 2018. Ant nurse
workers exhibit behavioural and transcriptomic signatures of specialization on larval
stage. Anim. Behav. 141, 161–169.
Walsh, J.T., Garnier, S., Linksvayer, T.A., 2019. Ant collective behavior is heritable and
shaped by selection. bioRxiv 567503. https://doi.org/10.1101/567503.
Wang, S., Sokolowski, M.B., 2017. Aggressive behaviours, food deprivation and the
foraging gene. R. Soc. Open Sci. 4, 170042.
Ward, P.S., 2014. The phylogeny and evolution of ants. Annu. Rev. Ecol. Evol. Syst. 45,
23–43.
Warner, M.R., Kovaka, K., Linksvayer, T.A., 2016. Late-instar ant worker larvae play a
prominent role in colony-level caste regulation. Insect. Soc. 63, 575–583.
Warner, M.R., Qiu, L., Holmes, M.J., Mikheyev, A.S., Linksvayer, T.A., 2019a. Convergent
eusocial evolution is based on a shared reproductive groundplan plus lineage-speciﬁc
plastic genes. Nat. Commun. 10, 2651.
Warner, M.R., Mikheyev, A.S., Linksvayer, T.A., 2019b. Transcriptomic basis and evo-
lution of the ant nurse-larval social interactome. PLoS Genet. 15, e1008156.
Wenseleers, T., et al., 2008. Cloning and expression of PKG, a candidate foraging reg-
ulating gene in Vespula vulgaris. Anim. Biol. Leiden Neth. 58, 341–351.
West-Eberhard, M.J., Jane, Mary, Senior Scientist West-Eberhard, Senior Scientist
Smithsonian Tropical Research Institute, 2003. Developmental Plasticity and
Evolution. OUP, USA.
Wilson, E.O., 1968. The ergonomics of caste in the social insects. Am. Nat. 102, 41–66.
Wilson, E.O., Hölldobler, B., 1988. Dense heterarchies and mass communication as the
basis of organization in ant colonies. Trends Ecol. Evol. 3, 65–68.
Winston, J.E., 2010. Life in the colonies: learning the alien ways of colonial organisms.
Integr. Comp. Biol. 50, 919–933.
Wissler, L., Gadau, J., Simola, D.F., Helmkampf, M., Bornberg-Bauer, E., 2013.
Mechanisms and dynamics of orphan gene emergence in insect genomes. Genome
D.A. Friedman, et al.
Hormones and Behavior 122 (2020) 104757
9

## Page 10

Biol. Evol. 5, 439–455.
Woodard, S.H., et al., 2011. Genes involved in convergent evolution of eusociality in bees.
Proc. Natl. Acad. Sci. U. S. A. 108, 7472–7477.
Wray, M.K., Mattila, H.R., Seeley, T.D., 2011. Collective personalities in honeybee co-
lonies are linked to colony ﬁtness. Anim. Behav. 81, 559–568.
Wright, C.M., et al., 2019. Collective personalities: present knowledge and new frontiers.
Behav. Ecol. Sociobiol. 73, 31.
Wu, F., et al., 2019. Behavioral, physiological, and molecular changes in alloparental care
givers may be responsible for selection response for female reproductive investment
in honey bees. Mol. Ecol. https://doi.org/10.1111/mec.15207.
Yan, H., et al., 2014. Eusocial insects as emerging models for behavioural epigenetics.
Nat. Rev. Genet. 15, 677–688.
D.A. Friedman, et al.
Hormones and Behavior 122 (2020) 104757
10


---
*Extraction method: pymupdf*