title: Epigenetic regulation of the honey bee transcriptome: unravelling the nature of methylated genes.
abstract: BACKGROUND
  Epigenetic modification of DNA via methylation is one of the key inventions in eukaryotic evolution. It provides a source for the switching of gene activities, the maintenance of stable phenotypes and the integration of environmental and genomic signals. Although this process is widespread among eukaryotes, both the patterns of methylation and their relevant biological roles not only vary noticeably in different lineages, but often are poorly understood. In addition, the evolutionary origins of DNA methylation in multicellular organisms remain enigmatic. Here we used a new 'epigenetic' model, the social honey bee Apis mellifera, to gain insights into the significance of methylated genes.
  
  
  RESULTS
  We combined microarray profiling of several tissues with genome-scale bioinformatics and bisulfite sequencing of selected genes to study the honey bee methylome. We find that around 35% of the annotated honey bee genes are expected to be methylated at the CpG dinucleotides by a highly conserved DNA methylation system. We show that one unifying feature of the methylated genes in this species is their broad pattern of expression and the associated 'housekeeping' roles. In contrast, genes involved in more stringently regulated spatial or temporal functions are predicted to be un-methylated.
  
  
  CONCLUSIONS
  Our data suggest that honey bees use CpG methylation of intragenic regions as an epigenetic mechanism to control the levels of activity of the genes that are broadly expressed and might be needed for conserved core biological processes in virtually every type of cell. We discuss the implications of our findings for genome-scale regulatory network structures and the evolution of the role(s) of DNA methylation in eukaryotes. Our findings are particularly important in the context of the emerging evidence that environmental factors can influence the epigenetic settings of some genes and lead to serious metabolic and behavioural disorders.
authors.affiliation: Centre for Bioinformation, Mathematical Sciences Institute, The Australian National University, Canberra ACT 0200, Australia. Sylvain.Foret@anu.edu.au
authors.forename: Sylvain
authors.initials: S
authors.lastname: Foret
authors.forename: Robert
authors.initials: R
authors.lastname: Kucharski
authors.forename: Yvonne
authors.initials: Y
authors.lastname: Pittelkow
authors.forename: Gabrielle A
authors.initials: GA
authors.lastname: Lockett
authors.forename: Ryszard
authors.initials: R
authors.lastname: Maleszka
mesh_terms: D000818:Animals; D001516:Bees / Q000235:genetics*; D019295:Computational Biology; D018899:CpG Islands; D019175:DNA Methylation; D044127:Epigenesis, Genetic; D020869:Gene Expression Profiling; D005786:Gene Expression Regulation; D017344:Genes, Insect; D049750:Genome, Insect; D020411:Oligonucleotide Array Sequence Analysis; D017422:Sequence Analysis, DNA