Honeybees are an important component of modern agricultural systems, and a fascinating and scientifically engrossing insect. Honeybees are not commonly used as model systems for understanding development in insects despite their importance in agriculture. Honeybee embryogenesis, while being superficially similar to Drosophila, is molecularly very different, especially in axis formation and sex determination. In later development, much of honeybee biology is modified by caste development, an as yet poorly understood, but excellent, system to study developmental plasticity. In adult stages, developmental plasticity of the ovaries, related to reproductive constraint exhibits another aspect of plasticity. Here they review the tools, current knowledge and opportunities in honeybee developmental biology, and provide an updated embryonic staging scheme to support future studies.

The absence of a full pedigree can hinder selective breeding efforts. In honeybees, definitive maternity and especially paternity of queens is difficult to determine, even under managed mating schemes (e.g. using artificial insemination) due to the negative effects of single-drone mating on colony fitness. Here we genotyped 388 living queens from two beekeeping operations using Genotyping-by-Sequencing (GBS). We evaluate two methods to call single-nucleotide polymorphism (SNPs), Tassel 5 and Stacks, for their ability to supply SNPs that can recover known relationships. While Stacks discovered more SNPs (29,433), SNPs called with Tassel 5 (16,757) were found to be more accurate for the derivation of relationships. This methodology presents a low-cost genotyping approach and can be used to support commercial honeybee breeding schemes.

Recent breakthroughs in gene-editing technologies that can render individuals fully resistant to infections may offer unprecedented opportunities for controlling future epidemics. Yet, their potential for reducing disease spread are poorly understood as the necessary theoretical framework for estimating epidemiological effects arising from gene editing applications is currently lacking. Here, we develop semi-stochastic modelling approaches to investigate how the adoption of gene editing may affect infectious disease prevalence in farmed animal populations and the prospects and time-scale for disease elimination. We apply our models to the Porcine Reproductive and Respiratory Syndrome PRRS, one of the most persistent global livestock diseases to date. Whereas extensive control efforts have shown limited success, recent production of gene-edited pigs that are fully resistant to the PRRS virus have raised expectations for eliminating this deadly disease. Our models predict that disease elimination on a national scale would be difficult to achieve if gene editing was used as the only disease control. However, when complemented with vaccination, the introduction of 10% of genetically resistant animals in a fraction of herds could be sufficient for eliminating the disease within 3-6 years. Besides strategic distribution of genetically resistant animals, several other key determinants underpinning the epidemiological impact of gene-editing were identified.

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