Machine Learning models identify gene predictors of waggle dance behaviour in honeybees

The molecular characterisation of complex behaviours is a challenging task as a range of different factors are often involved to produce the observed phenotype. An established approach is to look at the overall levels of expression of brain genes – known as ‘neurogenomics’ – to select the best candidates that associate with patterns of interest. This approach has relied so far on a set of powerful statistical tools capable to provide a snapshot of the expression of many thousands of genes that are present in an organism’s genome. However, traditional neurogenomic analyses have some well-known limitations; above all, the limited number of biological replicates compared to the number of genes tested – often referred to as “curse of dimensionality”. Here we implemented a new Machine Learning (ML) approach that can be used as a complement to established methods of transcriptomic analyses. We tested three types of ML models for their performance in the identification of genes associated with honeybee waggle dance. We then intersected the results of these analyses with traditional outputs of differential gene expression analyses and identified two promising candidates for the neural regulation of the waggle dance: the G-protein coupled receptor boss and hnRNP A1, a gene involved in alternative splicing. Overall, our study demonstrates the application of Machine Learning to analyse transcriptomics data and identify genes underlying social behaviour. This approach has great potential for application to a wide range of different scenarios in evolutionary ecology, when investigating the genomic basis for complex phenotypic traits.

Oscillations make a self-scaled model for honeybees’ visual odometer reliable regardless of flight trajectory

Honeybees foraging and recruiting nest-mates by performing the waggle dance need to be able to gauge the flight distance to the food source regardless of the wind and terrain conditions. Previous authors have hypothesized that the foragers’ visual odometer mathematically integrates the angular velocity of the ground image sweeping backward across their ventral viewfield, known as translational optic flow. The question arises as to how mathematical integration of optic flow (usually expressed in radians/s) can reliably encode distances, regardless of the height and speed of flight. The vertical self-oscillatory movements observed in honeybees trigger expansions and contractions of the optic flow vector field, yielding an additional visual cue called optic flow divergence. We have developed a self-scaled model for the visual odometer in which the translational optic flow is scaled by the visually estimated current clearance from the ground. In simulation, this model, which we have called SOFIa, was found to be reliable in a large range of flight trajectories, terrains and wind conditions. It reduced the statistical dispersion of the estimated flight distances approximately 10-fold in comparison with the mathematically integrated raw optic flow model. The SOFIa model can be directly implemented in robotic applications based on minimalistic visual equipment.

Honey bees show dance pattern to communicate – A review

The honey bee language is considered by many to be one of the most interesting systems for animal communications, used for recruitment to food sources. Honeybee's forager dancers communicate food and other resources to the household by quantity, consistency, direction, and spatial location. The waggle dance was interesting and complex, which bees used for spatial information on desired resources. All honeybee species use the waggle dance to convey their position and distance from food sources and possible new nest sites. The research was carried out on dance communication, earlier ideas, controversies, and solutions gave a broad overview. In this analysis, unique problems are focused on as follows: (a) multiple dance forms. (b) Distance and path calculation (c) How bees do dark hive dance.? Several experiments verified that bees perform various kinds of dance, depending on their particular task. There is, however, still a lack of comprehensive knowledge on other types of dances, which help us solve numerous questions and help us better understand the meaning of the different kinds of dances carried in and outside the hive by honeybees.

Parallel processing of olfactory and mechanosensory information in the honeybee antennal lobe.

We report that airflow produces a complex activation pattern in the antennal lobes of the honeybee Apis mellifera. Glomerular response maps provide a stereotypical code for the intensity and the dynamics of mechanical stimuli that is superimposed on the olfactory code. We show responses to modulated stimuli suggesting that this combinatorial code could provide information about the intensity, direction, and dynamics of the airflow during flight and waggle dance communication.

Honey Bees Extract Map Coordinates from the Dance

Honeybees communicate locations by the waggle dance, a symbolic form of information transfer. Here we ask whether the recruited bee uses only the indicated course vector or translates it into a location vector on a cognitive map. Recruits were captured on exiting the hive and displaced to distant release sites. Their flights were tracked by radar. Both the vector portions of their flights and the ensuing tortuous search portions were strongly and differentially affected by release site. Search patterns were biased toward the true location of the food and away from the location given by adding release-site displacement to the danced vector. The results imply that the bees recruited by the dance access the indicated location of the food on a shared spatial representation. Thus, the bee dance communicates two messages, a flying instruction and a map location.

The Electronic Bee Spy: Eavesdropping on Honeybee Communication via Electrostatic Field Recordings

As a canary in a coalmine warns of dwindling breathable air, the honeybee can indicate the health of an ecosystem. Honeybees are the most important pollinators of fruit-bearing flowers, and share similar ecological niches with many other pollinators; therefore, the health of a honeybee colony can reflect the conditions of a whole ecosystem. The health of a colony may be mirrored in social signals that bees exchange during their sophisticated body movements such as the waggle dance. To observe these changes, we developed an automatic system that records and quantifies social signals under normal beekeeping conditions. Here, we describe the system and report representative cases of normal social behavior in honeybees. Our approach utilizes the fact that honeybee bodies are electrically charged by friction during flight and inside the colony, and thus they emanate characteristic electrostatic fields when they move their bodies. These signals, together with physical measurements inside and outside the colony (temperature, humidity, weight of the hive, and activity at the hive entrance) will allow quantification of normal and detrimental conditions of the whole colony. The information provided instructs how to setup the recording device, how to install it in a normal bee colony, and how to interpret its data.

Do honey bee species differ in the odometer used for the waggle dance?

Honey bees estimate distances to food sources using image motion experienced on the flight path and they use this measure to tune the waggle phase duration in their dance communication. Most studies on the relationship between experienced optic flow and the dance-related odometer are based on experiments with Apis mellifera foragers trained into a small tunnel with black and white patterns which allowed quantifiable changes in the optic flow. In this study we determined the calibration curves for foragers of the two Asian honey bee species, A. florea and A. cerana, in two different natural environments with clear differences in the vegetation conditions and hence visual contrast. We found that the dense vegetation condition (with higher contrast) elicited a more rapid increase in the waggle phase duration with distance than the sparse vegetation in A. florea but not in A. cerana. Visual contrast did not affect the perception of the food reward, measured as the number of dance circuits produced per distance, in both species. Our findings suggest that contrast sensitivity of the waggle dance odometer, or other aspects of flight behaviour, might vary among honey bee species.