Exploring DNA Methylation Diversity in the Honey Bee Brain by Ultra-Deep Amplicon Sequencing

Robert Kucharski, Ryszard Maleszka

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Abstract

Understanding methylation dynamics in organs or tissues containing many different cell types is a challenging task that cannot be efficiently addressed by the low-depth bisulphite sequencing of DNA extracted from such sources. Here we explored the feasibility of ultra-deep bisulphite sequencing of long amplicons to reveal the brain methylation patterns in three selected honey bee genes analysed across five distinct conditions on the Illumina MiSeq platform. By combing 15 libraries in one run we achieved a very high sequencing depth of 240,000–340,000 reads per amplicon, suggesting that most of the cell types in the honey bee brain, containing approximately 1 million neurons, are represented in this dataset. We found a small number of gene-specific patterns for each condition in individuals of different ages and performing distinct tasks with 80–90% of those were represented by no more than a dozen patterns. One possibility is that such a small number of frequent patterns is the result of differentially methylated epialleles, whereas the rare and less frequent patterns reflect activity-dependent modifications. The condition-specific methylation differences within each gene appear to be position-dependent with some CpGs showing significant changes and others remaining stable in a methylated or non-methylated state. Interestingly, no significant loss of methylation was detected in very old individuals. Our findings imply that these diverse patterns represent a special challenge in the analyses of DNA methylation in complex tissues and organs that cannot be investigated by low-depth genome-wide bisulphite sequencing. We conclude that ultra-deep sequencing of gene-specific amplicons combined with genotyping of differentially methylated epialleles is an effective way to facilitate more advanced neuro-epigenomic studies in honey bees and other insects.
Original languageEnglish
Pages (from-to)1-10
Number of pages10
JournalEpigenomes
Volume4
Issue number2
DOIs
Publication statusPublished - 25 Jun 2020

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