Transcriptome-wide analysis uncovers regulatory elements of the antennal transcriptome repertoire of bumblebee at...

Bumblebees are crucial pollinators, providing essential ecosystem services and global food production. The success of pollination services relies on the interaction between sensory organs and the environment. The antenna functions as a versatile multi-sensory organ, pivotal in mediating chemosensory/olfactory information, and governs adaptive responses to environmental changes. Despite an increasing number of RNA-sequencing studies on insect antenna, comprehensive antennal transcriptome studies at the different life stages were not elucidated systematically. Here, we quantified the expression profile and dynamics of coding/microRNA genes of larval head and antennal tissues from early- and late-stage pupa to the adult of Bombus terrestris as suitable model organism among pollinators. We further performed Pearson correlation analyses on the gene expression profiles of the antennal transcriptome from larval head tissue to adult stages, exploring both positive and negative expression trends. The positively correlated coding genes were primarily enriched in sensory perception of chemical stimuli, ion transport, transmembrane transport processes and olfactory receptor activity. Negatively correlated genes were mainly enriched in organic substance biosynthesis and regulatory mechanisms underlying larval body patterning and the formation of juvenile antennal structures. As post-transcriptional regulators, miR-1000-5p, miR-13b-3p, miR-263-5p and miR-252-5p showed positive correlations, whereas miR-315-5p, miR-92b-3p, miR-137-3p, miR-11-3p and miR-10-3p exhibited negative correlations in antennal tissue. Notably, based on the inverse expression relationship, positively and negatively correlated microRNA (miRNA)-mRNA target pairs revealed that differentially expressed miRNAs predictively targeted genes involved in antennal development, shaping antennal structures and regulating antenna-specific functions. Our data serve as a foundation for understanding stage-specific antennal transcriptomes and large-scale comparative analysis of transcriptomes in different insects.