12. The future of Apis omics: Biological integration

In the coming decades, we anticipate the emergence of new methods driven by technological advances that will further reduce costs and expand omics applications beyond model species. At the moment, cutting-edge approaches, such as single-cell sequencing and atlas generation (Luecken & Theis, 2019; Misra et al., 2022), spatialomics (Moffitt et al., 2022), and the use of machine learning for various omics analyses  (Arjmand et al., 2022; Li et al., 2022) have been developed and applied for clinical and forensic purposes. These advancements hold great promise for honey bee research, offering unprecedented insights into the evolution of phenotypic plasticity, behavioral profiling within a superorganism, and the origins of eusociality.

However, immediate progress in our understanding of Apis honey bee biology, diversity, and evolution can be achieved by the layering of multi-omics data and interpretation (Toth & Zayed, 2021). Genomics, epigenomics, and transcriptomics have seen remarkable growth in honey bee research and provided valuable insights. By integrating multi-omics data from the same honey bee sample (single cell, tissue, individual or colony), we can uncover the mechanistic and immediate causes behind behavioral changes, such as labor division, as well as responses to various stress factors like pathogen infections or chemical exposure. The combination of multiple omics approaches has been proposed as a toolkit to better characterize and improve honey bee health (Grozinger & Zayed, 2020). Initiatives like the Canadian BeeCSI project are actively working on integrating multiple omics approaches to better understand and promote honey bee health.

The integration of behavioral assays, chemical profiling and metagenomics has shed light on the significance of honey bee host-microbiome interactions in nestmate recognition (Vernier et al., 2020). Leveraging functional genomics and transcriptomics, based on knowledge gained from studying the honey bee microbiome could help engineer innovative pathogen control methods (Leonard et al., 2020). As a last example, new insights in A. mellifera social immunity via the discovery of transmissible RNA in shared royal jelly resource, was made possible by the combination of proteomics, transcriptomics and functional genomics (Maori et al., 2019; Maori et al., 2019). Encouraged by these achievements, further multi-omics surveys are anticipated to expand our knowledge to other Apis species.