8.7. Transcriptomic analyses (“RNASeq”)
Transcriptomic analyses are helpful for seeing trends in honey bee gene expression as well as changes due to experimental conditions, and bee researchers have carried out such studies for many years, adapting as new methods arise. Two recent papers have used the ILLUMINA platform for studying gene regulation in response to nutrition (Alaux et al., 2011) and responsiveness to varroa mites and viruses (Nazzi et al., 2012), respectively. Analyzing RNASeq data will depend on the sequencing platform as well as developments in software and public or personal computational resources, all of which are under constant renewal. Generally, RNASeq experiments rely on differential gene expression (DGE) between categories of one factor (e.g., bees exposed to mites versus controls) and the statistical analysis identifies which regions are up- or down-regulated in the context of this factor. Nazzi et al., 2012 used a technique prescribed by Mortazavi et al., (2008) that, like all current methods, first develops a model for how often a particular expressed region should be seen in a sequencing effort, and then uses the number of times that sequence was sampled to determine whether it was up-or down regulated compared to an expected level. There are now numerous such methods and both methods and strategies to trim the computational resources for their use are being improved monthly. Public platform with video tutorials for RNASeq analysis that promises to remain current is described at the Galaxy site (https://main.g2.bx.psu.edu/).