Análisis de amenazas

At first glance, the networks derived here appear to be variable in gene composition, hub gene identity (Figure 4), and the overall interactions they describe (Figures 1-3). This apparent lack-of-convergence onto a single co-citation network, despite them

being inferred from essentially similar datasets (Table 1) suggests that honey bee workers can use different networks to control personal reproduction, perhaps as a function of age, environmental circumstance, or both. Given that workers use different sensory modalities to interact with and respond to changes in their environment, including their social environment (Tanaka and Hartfelder 2004; Cardoen et al. 2011a), it is conceivable that workers may use alternate or redundant pathways to control aspects of reproduction within colonies. Alternatively, a single pathway governing ovary activation in response to social cues seems more parsimonious (Amdam et al. 2006; Toth and Robinson 2007). If so, the multiple networks inferred here may represent segments of the larger, complete network that is still unknown. Different social and environmental signals may activate different suites of genes within this comprehensive network, explaining why the studies that vary in age, pheromone treatment, social structure, and environmental conditions have all captured different gene sets, with some degree of overlap.

The networks identified here represent hypotheses for how workers regulate their ovaries to control reproduction. Within the context of their eusocial colonies, this reproductive machinery is of direct significance to sociogenomic theory that postulates the existence of ‘genes for altruism’ (Hamilton 1963; Dawkins 1976). These genes have rarely been found (Thompson et al. 2013) but the networks presented here, together with other efforts to describe how genes interact with each other and with their cellular, physical and social environment (Bloch and Grozinger 2011; Wang et al. 2012), provide a starting point from which I can begin to test ideas

on the role of specific genes on reproductive phenotypes, including the prospect of finding genes for worker sterility. One approach might be to use functional genomic experiments that perturb hub genes or their neighbours, and then monitor worker phenotype. In particular it will be useful to measure how knock-outs affect worker phenotypes related to reproduction, including response to queen mandibular pheromone, ovary activation and egg laying, as well as other measures of social divisions in labour such as nurse-to-forager transitions or forager specializations. Finally, I suggest that future studies incorporate co-expression information and honey bee protein interactions, so that networks can then be made from Apis genes directly without the need for conversion to Drosophila, and would not rely on the somewhat haphazard availability of co-citation data in PubMed. The presence of the dopamine, insulin, and ecdysteroid signaling pathways suggests that gene interaction studies will play an important role in uncovering the main endocrine and neuronal control mechanisms that ultimately regulate ovarian physiology and altruistic behaviour in honey bee workers.

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3. Discussion

The goal of this thesis was to take the well-founded conceptual framework of kin selection and apply it empirically to the honey bee in a case study for reproductive altruism. In Chapter 1, I outlined seven predicted characteristics of ‘genes for altruism’ and illustrated the progress with evidence in the honey bee to date. In Chapter 2, I addressed one prediction specifically – that genes for altruism should be environmentally sensitive – by generating gene networks from published microarray data. Specifically, these networks were constructed using worker gene expression differences upon exposure to queen pheromone, in an effort to better understand the genetic interactions underlying worker sterility and uncover genes involved in reproductive altruism. In this final discussion, I would like to outline some of the challenges, caveats, and future directions with using a brand new co-citation network approach to understanding honey bee sterility.

I predicted my meta-analysis approach of using multiple studies, each slightly varying in experimental design, would yield a set of recurring gene interactions that reveal the main pathway for reproductive regulation. Instead, I found that the gene networks had little genetic overlap, yet they all retained similar functions. If these low levels of gene overlap were due to strictly biological reasons, then this finding will lead to new theories of why and how workers evolved multiple gene networks to govern their reproduction. However, this overlap was likely due to a combination of biological and technical reasons, and now I would like to evaluate the approach of building co- citation networks from several microarrays using fruit fly homologs.