Apidologie Review article * INRA, DIB and Springer-Verlag France, 2013 DOI: 10.1007/s13592-013-0251-4 Honey bee sociogenomics: a genome-scale perspective on bee social behavior and health 1 1,2 Adam G. DOLEZAL , Amy L. TOTH 1Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, IA, USA 2Department of Entomology, Iowa State University, Ames, IA, USA Received 3 July 2013 – Revised 9 October 2013 – Accepted 18 October 2013 Abstract – The biology of honey bees involves a host of developmental, behavioral, and physiological components that allow thousands of individual bees to form complex social units. Fueled by a wealth of information from new genomic technologies, a new approach, sociogenomics, uses a focus on the genome to integrate the molecular underpinnings and ultimate explanations of social life. This approach has resulted in a massive influx of data from the honey bee genome and transcriptome, a flurry of research activity, and new insights into honey bee biology. Here, we provide an up-to-date review describing how the honey bee has been successfully studied using this approach, highlighting how the integration of genomic information into honey bee research has provided insights into worker division of labor, communication, caste differences and development, evolution, and honey bee health. We also highlight how genomic studies in other eusocial insect species have provided insights into social evolution via comparative analyses. These data have led to several important new insights about how social behavior is organized on a genomic level, including (1) the fact that gene expression is highly dynamic and responsive to the social environment, (2) that large-scale changes in gene expression can contribute to caste and behavioral differences, (3) that transcriptional networks regulating these behaviors can be related to previously established hormonal mechanisms, and (4) that some genes and pathways retain conserved roles in behavior across contexts and social insect taxa. genome / division of labor / behavioral maturation / caste / comparative genomics 1. INTRODUCTION approaches to bridge gaps between evolutionary and mechanistic approaches to studying ani- The social life of bees has been of intense mal societies began little more than a decade interest to biologists and apiculturists for centu- ago. ries. As such, there has been a wealth of studies This new approach, dubbed sociogenomics on the evolution, behavior, colony organization, (Robinson 1999), proposed that the genome can and development of honey bees and their form a centerpiece for linking different levels of societies. These studies have spanned across analysis, allowing researchers to integrate the levels of analysis, providing insight into both proximate causes of behavior, like gene expres- the proximate and ultimate causes behind the sion and physiology, with more ultimate analy- social complexity of honey bee society. ses, like behavioral ecology. By using the However, specific focus on integrating these genome as a focal point, sociogenomics seeks to provide a more comprehensive method for understanding social life, from its evolution to — Corresponding author: A. Dolezal, its genetic regulation and everywhere in be- [email protected] tween (Robinson et al. 2005). Since studies on Manuscript editor: Stan Schneider honey bees have historically run the gamut A.G. Dolezal and A.L. Toth across these levels of analysis, it is unsurprising disease and pathogen responses. Finally, while we that bees have become an important model for focus specifically on how sociogenomics has applying sociogenomic approaches. With the improved our understanding of bee biology, increased scope and availability of genomic throughout the review, we highlight how a tools (Table I), including the sequencing of the sociogenomic-minded exploration across social complete honey bee genome (Weinstock et al. insect taxa has fueled comparisons for a better 2006), studies grounded in a genomic perspec- understanding of the evolution of eusociality. tive have been successful in helping to tease apart the different components that intersect to 2. WORKER DIVISION OF LABOR build complex social organisms (Smith et al. 2008). 2.1. Foraging ontogeny The sociogenomic approach spans across a large swathe of applications and has been One of the most striking aspects of eusocial defined broadly (Robinson et al. 2005). Here, insect societies, and honey bees in particular, is we restrict our definition to research focusing the behavioral plasticity found within the on large numbers of genes or on single genes worker caste. This flexibility takes the form of that provide key insights into larger genetic temporal polyethism, in which workers transition pathways, and exclude a rich and informative across different task repertoires as they age. After literature on single genes (e.g., Ben-Shahar adult emergence, workers specialize on a variety 2005; Amdam et al. 2010) that are beyond the of in-nest tasks, such as brood care, and then scope of this review. We focus our review on transition through stages of other tasks, such as large-scale genomic or transcriptomic analy- nest maintenance and guarding, culminating in ses, microarrays, or targeted studies that foraging behavior (Winston 1987). While this explore or clarify genetic pathways consisting sequence of behavioral maturation occurs as a of multiple genes. Furthermore, while we focus general pattern, workers exhibit a high level of specifically on how the rise of sociogenomics flexibility in the rate of behavioral development, has helped us understand the social life of bees, which allows individuals to respond to differing this approach has been very successful in other colonial demands (Robinson 1992). eusocial insects (Smith et al. 2008). In fact, one At this point in time, sociogenomics has been important strength of sociogenomics is the more thoroughly applied to the study of worker capability to make comparisons: the power to behavioral maturation than any other facet of search for homologies in genomes across taxa honey bee biology and, therefore, stands as the helps find clues to understand the evolution of best example of how successful this approach can bee societies (Fischman et al. 2011). be. This is largely due to the strong background of Here, we review how the use of sociogenomics literature and expertise spanning behavioral, has advanced knowledge of many facets of honey genetic, neurobiological, and physiological bee biology. We begin with worker temporal studies on temporal polyethism, which has allowed polyethism; the behavioral transition from in-hive researchers to build a more comprehensive to foraging tasks is arguably the best studied understanding of this system centering on honey bee behavioral phenomenon using a investigation of the genome (Robinson 2002; sociogenomic approach, and we use it as a Robinson et al. 2005; Smith et al. 2008)(Figure1). benchmark for comparison with other research Before sequencing of the honey bee genome, foci. Then, we follow with descriptions of the most of the studies described as sociogenomic progress made in understanding the evolution and were borne from the integration of behavioral, regulation of caste differences, communication, neuronal, and physiological mechanisms with and social immunity, and we also review how the genomic information generated from partial approaches and methods pioneered with genome resources, which provided vastly more sociogenomics have been applied to honey bee information than previous approaches that focused Table I. How has the sequencing of the honey bee genome changed sociogenomic applications? Application Pre-genome Post-genome Gain from genome References Gene discovery e.g., Degenerate polymerase Computational analysis Whole genome instead Elsik, Mackey et al. (2007) chain reaction (PCR) and of entire genome sequence of single gene, less cloning on a gene-by-gene labor-intensive, allows basis discovery of novel genes Identification of e.g., Rapid amplification of Computational analysis of Whole genome instead Ament et al. (2012b) regulatory sequences cDNA ends on a gene-by- entire genome sequence, of single gene, less gene basis chromatin immunoprecipitation labor-intensive and sequencing Epigenetic profiling e.g., Methylation sensitive Computational analysis of Ability to identify actual Kronforst, Gilley et al. (e.g., identifying amplified fragment length CpG observed/expected content genes and nucleotides (2008); Herb et al. (2012) methylation) polymorphism of anonymous of genome, whole genome that are methylated, Honey bee sociogenomics methylated sites bisulfite sequencing whole genome coverage instead of a small subset Gene expression Quantitative PCR for select Whole-genome microarrays, Whole genome instead of Whitfield et al. (2002, 2003); profiling genes, EST-based microarrays, RNA sequencing compared a fraction of the genome, Chen et al. (2012); Liang screening ESTs for a small to whole genome RNA-Seq is less labor- et al. (2012) number of differentially intensive and has a greater expressed genes dynamic range Sequence evolution Complex sequence of molecular Bioinformatic comparisons Whole genome instead of Hunt et al. (2010); Johnson techniques, with the ability to across species that include select genes, enhanced and Tsutsui (2011) target only a small number numerous genes and entire ability to uncover gene of genes gene families losses and gains Many studies on honey bee sociogenomics occurred before