Meta-Analysis of the Public RNA-Seq Data of the Western Honeybee Apis mellifera to Construct Reference Transcriptome Data

SIMPLE SUMMARY: The honeybee is an economically and ecologically essential insect species and a critical social behavior model. It is vital to honey production and pollination. Therefore, it has been studied extensively in entomological research. The Western honeybee (Apis mellifera) is a representative species of honeybees. Reference transcriptome data are required to perform the meta-analyses using public RNA-Seq data and transcriptome analysis using newly sequenced RNA-Seq data. The reference transcriptome sequences were constructed, which consisted of 149,685 transcripts, and 194,174 predicted amino acid sequences. Half the predicted protein sequences were functionally annotated using protein sequence datasets for several model and insect species. We performed meta-analysis to search for novel immune-response-related transcripts. We identified 3–20 transcripts that were upregulated or downregulated in response to both viral and bacterial infections. However, the immune-related transcripts were not included among them. Autophagy-related protein 3 was downregulated by viral infections. The results suggested that autophagy was implicated in the viral immune responses, and autophagy was not regulated by the canonical immune pathways in A. mellifera. The results of the meta-analysis suggested that the reference transcriptome data could be used for transcriptome analysis in A. mellifera. ABSTRACT: The Western honeybee (Apis mellifera) is valuable in biological research and agriculture. Its genome sequence was published before those for other insect species. RNA-Seq data for A. mellifera have been applied in several recently published studies. Nevertheless, these data have not been prepared for use in subsequent meta-analyses. To promote A. mellifera transcriptome analysis, we constructed reference transcriptome data using the reference genome sequence and RNA-Seq data curated from about 1,000 runs of public databases. The new reference transcriptome data construct comprised 149,685 transcripts, and 194,174 protein sequences were predicted. Approximately 50–60% of the predicted protein sequences were functionally annotated using the protein sequence data for several model and insect species. Novel candidate immune-related transcripts were searched by meta-analysis using immune-response-related RNA-Seq and reference transcriptome data. Three to twenty candidate transcripts including autophagy-related protein 3 were upregulated or downregulated in response to both viral and bacterial infections. The constructed reference transcriptome data may facilitate future transcriptome analyses of A. mellifera.