Transcriptome analysis for investigating dormancy in highly eusocial bees

Abstract

Many species exhibit seasonal adaptive behaviors that are associated with adverse environmental conditions. One key strategy employed is dormancy, which is characterized by arrest of development or activities, frequently accompanied by metabolic suppression. The stingless bees, the highly eusocial group Meliponini, from the subtropical region of Brazil, such as Plebeia remota and Melipona marginata, tolerate low temperatures during the winter, while species from the Brazilian semiarid region, such as Melipona subnitida, tolerate high temperatures and drought. P. remota and M. marginata exhibit the adaptive behavior known as reproductive diapause, which is characterized as a programmed arrest in the egg-laying and foraging for food to feed larvae. The species M. subnitida exhibit the adaptive strategy known as aestivation/quiescence, which is characterized in this species by a reduction in the construction of brood cells and a decrease in foraging during the hot and dry months. Another highly eusocial bee species that undergoes dormancy is Apis mellifera (Apini). In temperate climates, they arrest the brood production during the winter, while in tropical climates, there is a reduction in brood production during cool and wet months. Although progress has been made in describing these behaviors, a lack of the molecular basis underlying dormancy in bees and other insects, particularly those from/in the Neotropical region still persists. Therefore, the objective of my PhD is to prospect genes differentially expressed during the reproductive diapause in P. remota and M. marginata and aestivation in M. subnitida. Furthermore, a comparison of the transcripts will be performed to verify if there is a common set of genes that support the dormancy in the species. This BEPE project aims to improve my findings by using the bioinformatics tools performed in the laboratory of Dr. Christina Grozinger but not yet conducted in our own laboratory, such as: WGCNA and machine learning for comparative analyses among different studied species of stingless bees. Additionally, we will investigate tissue-specific transcriptional patterns of dormancy in A. mellifera in Brazil (tropical climate) and compare it with data obtained by her team in the United States (temperate climate), and further compare the results of these studies with our data from stingless bees. Therefore, the collaboration with Dr Grozinger research group will enrich our study by discussing our findings and expand our expertise in bioinformatics analyses.