Modeling methyl-sensitive transcription factor motifs with an expanded epigenetic alphabet
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ABSTRACT:
ORGANISM(S): Mus musculus
PROVIDER: GSE198458 | GEO | 2022/08/16
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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Project description:Genomic analyses often involve scanning for potential transcription-factor (TF) binding sites using models of the sequence specificity of DNA binding proteins. Many approaches have been developed to model and learn a protein’s binding specificity by representing sequence motifs, including the gaps and dependencies between binding-site residues, but these methods have not been systematically compared. Here we applied 26 such approaches to in vitro protein binding microarray data for 66 mouse TFs belonging to various families. For 9 TFs, we also scored the resulting motif models on in vivo data, and found that the best in vitro–derived motifs performed similarly to motifs derived from in vivo data. Our results indicate that simple models based on mononucleotide position weight matrices learned by the best methods perform similarly to more complex models for most TFs examined, but fall short in specific cases. In addition, the best-performing motifs typically have relatively low information content, consistent with widespread degeneracy in eukaryotic TF sequence preferences. Protein binding microarray (PBM) experiments were performed for a set of 86 mouse transcription factors. Briefly, the PBMs involved binding GST-tagged DNA-binding proteins to two double-stranded 44K Agilent microarrays, each containing a different DeBruijn sequence design, in order to determine their sequence preferences. Details of the PBM protocol are described in Berger et al., Nature Biotechnology 2006.
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