The integrative analysis of microRNA and mRNA expression in Apis mellifera following maze-based visual pattern learning

Qiu Hong Qin, Zi Long Wang, Liu Qing Tian, Hai Yan Gan, Shao Wu Zhang, Zhi Jiang Zeng*

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    29 Citations (Scopus)

    Abstract

    The honeybee (Apis mellifera) is a social insect with strong sensory capacity and diverse behavioral repertoire and is recognized as a good model organism for studying the neurobiological basis of learning and memory. In this study, we analyzed the changes in microRNA (miRNA) and messenger RNA (mRNA) following maze-based visual learning using next-generation small RNA sequencing and Solexa/lllumina Digital Gene Expression tag profiling (DGE). For small RNA sequencing, we obtained 13 367 770 and 13 132 655 clean tags from the maze and control groups, respectively. A total of 40 differentially expressed known miRNAs were detected between these two samples, and all of them were up-regulated in the maze group compared to the control group. For DGE, 5 681 320 and 5 939 855 clean tags were detected from the maze and control groups, respectively. There were a total of 388 differentially expressed genes between these two samples, with 45 genes up-regulated and 343 genes down-regulated in the maze group, compared to the control group. Additionally, the expression levels of 10 differentially expressed genes were confirmed by quantitative reverse transcription polymerase chain reaction (qRT-PCR) and the expression trends of eight of them were consistent with the DGE result, although the degree of change was lower in amplitude. The integrative analysis of miRNA and mRNA expression showed that, among the 40 differentially expressed known miRNAs and 388 differentially expressed genes, 60 pairs of miRNA/mRNA were identified as co-expressed in our present study. These results suggest that both miRNA and mRNA may play a pivotal role in the process of learning and memory in honeybees. Our sequencing data provide comprehensive miRNA and gene expression information for maze-based visual learning, which will facilitate understanding of the molecular mechanisms of honeybee learning and memory.

    Original languageEnglish
    Pages (from-to)619-636
    Number of pages18
    JournalInsect Science
    Volume21
    Issue number5
    DOIs
    Publication statusPublished - 1 Oct 2014

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