Healthy bees are a crucial part of our global food security. In fact, bees are so beneficial to the agricultural sector that their economic value is about $15 billion annually in the US alone. Many of the nuts, fruits and vegetables we eat every day are pollinated by bees, not to mention the canola, rapeseed and even the coffee we drink. Honey bees (Apis mellifera) are given most of the credit for this, but other species are also beneficial; for example, the alfalfa and canola industries use the leaf-cutter bee (Megachile rotundata) and many greenhouse operations employ bumble bees (Bombus spp.). Depending on the region and the crop, many other wild bees also contribute to agricultural pollination. But today, bees are facing many challenges, including pathogens, parasites and pesticides, and modern ‘omics technology has emerged as an excellent tool to help disentangle how complex interacting factors are affecting bee health.
With bee ‘omics research on the rise, Judith Trapp and Alison McAfee (in the Foster Lab within the CBR) saw an opportunity to review how recent genomic, transcriptomic and proteomic research is shaping our understanding of bees amidst today’s global trends. In their timely Molecular Ecology article, Trapp and McAfee discuss how the ‘omics toolkit is helping us understand and combat bee diseases. For example, in other species, such as cattle, corn and rice, breeders use genetic markers to select for beneficial traits. But since bees have incredibly high rates of genetic recombination, links between DNA markers and traits quickly decay. This has led proteomics to become an indispensable tool for breeding disease-resistant bees. Trapp and McAfee also offer their perspectives on the future of bee research and major holes that need to be filled, namely, revamping the genome annotation.
Once a genome is assembled, the first step is identifying the genes it contains and assigning their respective functions, i.e. “annotating the genome”, in part because virtually all other ‘omics tools – proteomics included – rely on having a complete, accurate gene set. However, annotating bee genomes is a surprisingly challenging process. It has been over a decade since the first bee genome was sequenced, but its unconventional properties continue to challenge even the best gene prediction algorithms. Some of the newly sequenced genomes are similarly challenging. However, a much bigger problem in bees is that once genes are identified, it is hard to know exactly what they do. Similar sequences tend to have similar functions. If a sequence in a new species matches one we already know in a different species, this information can be used to infer the function (also known as ‘orthology delineation’). The problem with bees, though, is that they are very different from any of the well-annotated species. Fruit flies are the closest match, but even they diverged from bees ~300 million years ago. To put this into perspective, this is about the same as the genetic distance between mammals and birds. As a result, anywhere from 10 to 20% of genes across bee species currently have unknown functions.
As it stands, Trapp and McAfee argue that we are due to upgrade the current annotation and this needs to be a top priority in the bee research community. Foster’s own research group is embarking on a project to better annotate gene structures (primarily splice isoforms), but the sheer number of genes with unknown functions calls for a concerted community-wide effort to decipher their roles (e.g. using publically available data combined with targeted gene manipulations). Not only will it improve the quality of research done on honey bees, but it will also pave the way for similar endeavours with the newly sequenced bee species and others yet to be sequenced.