About this Research Topic
The discovery of heritable DNA base modification by methylation and chemical modifications on chromatin have established the foundation of studying these epigenetic modifications on a genome-wide scale. Dynamic changes in epigenome are curial in normal development during organogenesis and homeostasis, as well as in diseases such as age-related tissue degeneration and cancer. The recent advent of single-cell genomics has promoted our understanding of epigenetic regulations in single-base and single-cell resolution, which allows the discovery of spatial organization and intercellular interactions in various biological models. Integration of epigenome data with different -omics datasets facilitates multimodal omics measurements, creating a powerful way to analyze a biological event from different perspectives. Yet these powerful genomics approaches come with complex experimental and analytical setup that many biomedical scientists find it challenging.
The aim of the current Research Topic is to provide representative single-cell level epigenome studies in developmental models, including epigenetic regulations in cell fate control and lineage determination, the contribution of environmental epigenomics in health and disease, and technical aspects such as constructing precise molecular timelines for understanding the role of epigenetics in gene regulation. Cutting-edge single-cell experimental approaches such as single-cell DNA methylome sequencing, single-cell ATAC-seq and single-cell ChIP-seq will be covered. It will provide readers novel views on epigenetic regulations in development and applied single-cell analysis in their research.
• Decoding dynamic epigenetic modifications in development through single-cell epigenomic approaches, such as identification of epigenetic regulations in cell lineage and cell fate determination.
• Decoding of epigenetic regulations in aging, cancer or tissue regeneration.
• In vivo and In vitro model systems for single-cell epigenome analysis
• Application of epigenome data in single-cell multimodal omics
• Novel single-cell genomic methods in experimental and bioinformatics applications
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