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DeepH&M: Simultaneous determination of single-CpG hydroxymethylation and methylation levels from enrichment and restriction enzyme sequencing methods

ABSTRACT: Increased appreciation of 5-hydroxymethylation (5hmC) as a stable epigenetic mark, which defines cell identity and disease progress, has engendered a need for cost-effective, but high-resolution 5hmC mapping technology. Current enrichment-based technologies provide cheap, but low-resolution and relative enrichment of 5hmC levels while single base-resolution methods can be prohibitively expensive to scale up to large experiments. To address this problem, we developed a deep learning-based method “DeepH&M”, which integrates enrichment and restriction enzyme sequencing methods to simultaneously estimate absolute hydroxymethylation and methylation levels at single CpG resolution. Using 7-week-old mouse cerebellum data for training DeepH&M model, we demonstrated that the 5hmC and 5mC levels predicted by DeepH&M were in high concordance with gold standard data predicted by TAB-seq and WGBS. The DeepH&M model can be applied to 7-week old frontal cortex and 79-week cerebellum revealing the robust generalizability of this method to other tissues from various biological time points.

ORGANISM(S): Mus musculus

PROVIDER: GSE140125 | GEO | 2020/09/10

REPOSITORIES: GEO

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Project description:DNA hydroxymethylation (5hmC) represents a new layer of epigenetic regulation in addition to DNA methylation (5mC). The genome-wide patterns of 5hmC distribution in many tissues and cells have recently been revealed by hydroxymethylated DNA immunoprecipitation (hMeDIP) followed by high throughput sequencing or tiling arrays. However, the DNA hydroxymethylome data generated by the conventional hMeDIP-seq method can not be used for direct quantitative comparison across different samples. In this study, we report a new quantitative hMeDIP-seq method, which uses barcode technology to label different DNA samples and performs hMeDIP-seq for multiple samples in one reaction system. Using this new method, we profiled and compared the DNA hydroxymethylomes of mouse ES cells (ESCs) and mouse ESCs-derived neural progenitor cells (NPCs). 5hmC levels around TSS in either ESCs or NPCs had negative correlation with gene expression levels，while 5hmC levels at gene body regions had different correlation with gene expression, depending on cell types. We identified differential hydroxymethylated regions (DHMRs) by comparing the 5hmC density of all 5hmC peaks between ESCs and NPCs. Many selected DHMRs (e.g., Ankrd23, Hist1h2aa, Fbxw7, and Epha2) were validated by hMeDIP-qPCR. Furthermore, we analyzed the relationship between the alteration of DNA hydroxymethylation and the gene expression change during neural differentiation, and our data suggest that both up- and down-regulated genes exhibited dramatic decrease in 5hmC during neural differentiation while the alteration of 5hmC had weak positive correlation with the changes in gene expression. Taken together, our data demonstrate that quantitative hMeDIP-seq is a powerful approach for genome-wide comparison of DNA hydroxymethylation across multiple samples. Importantly, the DHMRs between ESCs and NPCs uncovered in this study may provide clues for further investigation of the function of 5hmC in gene regulation and neural differentiation. Comparision of the genome-wide distribution of 5hmC in mouse embryonic stem cells and mouse ES-derived neural progenitor cells.

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DeepH&M: Simultaneous determination of single-CpG hydroxymethylation and methylation levels from enrichment and restriction enzyme sequencing methods

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