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

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.

SUBMITTER: Kucharski R

PROVIDER: S-EPMC8594699 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BACKGROUND: Deep sequencing of viruses isolated from infected hosts is an efficient way to measure population-genetic variation and can reveal patterns of dispersal and natural selection. In this study, we mined existing Illumina sequence reads to investigate single-nucleotide polymorphisms (SNPs) within two RNA viruses of the Western honey bee (Apis mellifera), deformed wing virus (DWV) and Israel acute paralysis virus (IAPV). All viral RNA was extracted from North American samples of honey bees or, in one case, the ectoparasitic mite Varroa destructor. RESULTS: Coverage depth was generally lower for IAPV than DWV, and marked gaps in coverage occurred in several narrow regions (< 50 bp) of IAPV. These coverage gaps occurred across sequencing runs and were virtually unchanged when reads were re-mapped with greater permissiveness (up to 8% divergence), suggesting a recurrent sequencing artifact rather than strain divergence. Consensus sequences of DWV for each sample showed little phylogenetic divergence, low nucleotide diversity, and strongly negative values of Fu and Li's D statistic, suggesting a recent population bottleneck and/or purifying selection. The Kakugo strain of DWV fell outside of all other DWV sequences at 100% bootstrap support. IAPV consensus sequences supported the existence of multiple clades as had been previously reported, and Fu and Li's D was closer to neutral expectation overall, although a sliding-window analysis identified a significantly positive D within the protease region, suggesting selection maintains diversity in that region. Within-sample mean diversity was comparable between the two viruses on average, although for both viruses there was substantial variation among samples in mean diversity at third codon positions and in the number of high-diversity sites. FST values were bimodal for DWV, likely reflecting neutral divergence in two low-diversity populations, whereas IAPV had several sites that were strong outliers with very low FST. CONCLUSIONS: This initial survey of genetic variation within honey bee RNA viruses suggests future directions for studies examining the underlying causes of population-genetic structure in these economically important pathogens.

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

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