Study of differential gene expression in queen, drone and worker honey bee using RNA-seq data

Document Type : Research Paper


1 Former M. Sc. Student, College of Agriculture & Natural Resources, University of Tehran, Karaj, Iran

2 Assistant Professor, College of Agriculture & Natural Resources, University of Tehran, Karaj, Iran

3 Assistant Professor, Animal Science Research Institute of Iran (ASRI), Karaj, Iran


The aim of this study was to investigate the gene expression profile and find the important genes in the differentiation and evolution of the queen, worker and drone honey bee at Stage 5 Larvae. Therefore, transcripts (total mRNA sequence) of 15 samples of Italian honey bee (A. m. ligustica) including 5 drone, 5 worker and 5 queen bees were aligned to the reference genome of the honey bee. In gene expression analysis of RNA-Seq data, 15962 genes and 31297 isoforms were identified. In our differential gene expression analyses, 465 genes between drone and queen bees, 495 genes between worker and queen bees and 764 genes between drone and worker bees, were expressed differently (P <0.000005). The largest difference in expression of genes was observed between drone and workers were for GB45614 and GB42053, with log2 fold change that was -10 and 11.5, respectively. In drone and queen bees comparison, GB45614 and GB48020 genes with log2 fold change 7.11 and 8.11, and in queen and worker bees comparison, GB43508 and GB42053 with log2 fold change 6.6 and -9, had the largest difference in gene expression, respectively. The analysis of the gene ontology (GO) and the pathways involved showed that the function of many of these genes has yet to be found. However, a large number of the genes expressed defiantly in drone and queen bees were related to integral component of membrane, calcium ion binding, carboxypeptidase, cholecystokinin receptor,chitin metabolic process, chymotrypsin inhibitor, haemolymph juvenile hormone binding and pupal cuticle protein, while differentially expressed genes in queen and worker bees comparison were related to metabolic pathways, enzymes metabolism, Pyrimidine metabolism, lipid metabolism, protein kinase, ATP binding and nucleic acid, intracellular cholesterol transport, chitin metabolic process, nitrogen compound metabolic process, hydrolase activity and chitin binding. The genes expressed at different levels in worker bees and drones were related to structural elements, the metabolism membrane and transfer of amino acids, calcium-ion-bound, ion-binder, intracellular cholesterol transport and chitin metabolism.


  1. Andrews, S. (2010). FastQC: a quality control tool for high throughput sequence data. From:
  2. Banabazi, M. H., Naserkheil, M. & Miraei-Ashtiani, S. R. (2012a). Network regulatory Gene expreesion of cerevisiae cell cycle with correlation weight method. The third national conference on agricultural biotechnology Iran. Ferdowsi University of Mashhad. (in Farsi)
  3. Banabazi, M. H., Naserkheil, M. & Miraei-Ashtiani, S. R. (2012b). Algorithm to identify genes expressed differently in the yeast Saccharomyces cerevisiae microarray data using software packages R. The third national conference on agricultural biotechnology Iran. Ferdowsi University of Mashhad. (in Farsi)
  4. Barchuk, A. R., Cristino, A. S., Kucharski, R., Costa, L. F., Simões, Z. L. & Maleszka, R. (2007). Molecular determinants of caste differentiation in the highly eusocial honeybee Apis mellifera. BMC Developmental Biology, 7(1), 70.
  5. Bolger, A. M., Lohse, M. & Usadel, B. (2014). Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics, 30(15), 2114-2120.
  6. Park, D., Jung, J. W., Choi, B. S., Jayakodi, M., Lee, J., Lim, J., ... & Choi, I. Y. (2015). Uncovering the novel characteristics of Asian honey bee, Apis cerana, by whole genome sequencing. BMC Genomics, 16(1), 1.
  7. Ekblom, R. & Galindo, J. (2010). Applications of next generation sequencing in molecular ecology of non-model organisms. Heredity, 107(1), 1-15.
  8. Gan, Q., Chepelev, I., Wei, G., Tarayrah, L., Cui, K., Zhao, K. & Chen, X. (2010). Dynamic regulation of alternative splicing and chromatin structure in Drosophila gonads revealed by RNA-seq. Cell Research, 20(7),763-783.
  9. Haas, B. J. & Zody, M. C. (2010). Advancing RNA-seq analysis. Nature Biotechnology, 28(5), 421.
  10. He, X.-J., Jiang, W.-J., Zhou, M., Barron, A. B. & Zeng, Z.-J. (2017). A comparison of honeybee (Apis mellifera) queen, worker and drone larvae by RNA-Seq. Insect Science
  11. Langmead, B. & Salzberg, S. (2012). Fast gapped-read alignment with Bowtie 2. Nature Methods 9, 357-359.
  12. Li, H. & Durbin, R. (2009). Fast and accurate short read alignment with Burrows–Wheeler transform. Bioinformatics, 25(14), 1754-1760.
  13. Goff, L. A., Trapnell, C. & Kelley, D. (2012). CummeRbund: visualization and exploration of Cufflinks high-throughput sequencing data. R Package Version, 2(0).
  14. Marguerat, S. & Bähler, J. (2010). RNA-seq: from technology to biology. Cellular and Molecular Life Sciences, 67(4), 569-579.
  15. Mortazavi, A., Williams, B., McCue, K., Schaeffer, L. & Wold, B. (2008). Mapping and quantifying mammalian transcriptomes by RNA-Seq. Nature Methods, 5(7), 621-628.
  16. Ashby, R., Forêt, S., Searle, I. & Maleszka, R. (2016). MicroRNAs in honey bee caste determination. Scientific Reports, 6, 18794.
  17. Sultan, M., Schulz, M. H., Richard, H., Magen, A., Klingenhoff, A., Scherf, M. & Schmidt, D. (2008). A global view of gene activity and alternative splicing by deep sequencing of the human transcriptome. Science, 321(5891), 956-960.
  18. Tahmasebi, Gh. & Porgharaei, H. (2000). Investigating the role of bee in pollination and increasing the production of agricultural products in Iran
  19. Wilhelm, B. T. & Landry, J. R. (2009). RNA-Seq-quantitative measurement of expression through massively parallel RNA-Sequencing. Methods, 48, 249-257.
  20. Wu, X. B., Wang, Z. L., Gan, H. Y., Li, S. Y. & Zeng, Z. J. (2016). Transcriptome comparison between newly emerged and sexually matured bees of Apis mellifera. Journal of Asia-Pacific Entomology, 19(3), 893-897.