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Mol. Cells 2023; 46(2): 86-98

Published online February 27, 2023

https://doi.org/10.14348/molcells.2023.0013

© The Korean Society for Molecular and Cellular Biology

Epigenetic Regulations in Mammalian Cells: Roles and Profiling Techniques

Uijin Kim and Dong-Sung Lee*

Author Info. +

Department of Life Science, University of Seoul, Seoul 02504, Korea

Correspondence to : eaststar0@gmail.com

Received: January 14, 2023; Revised: February 3, 2023; Accepted: February 4, 2023

This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-sa/3.0/.

Abstract

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The genome is almost identical in all the cells of the body. However, the functions and morphologies of each cell are different, and the factors that determine them are the genes and proteins expressed in the cells. Over the past decades, studies on epigenetic information, such as DNA methylation, histone modifications, chromatin accessibility, and chromatin conformation have shown that these properties play a fundamental role in gene regulation. Furthermore, various diseases such as cancer have been found to be associated with epigenetic mechanisms. In this study, we summarized the biological properties of epigenetics and single-cell epigenomic profiling techniques, and discussed future challenges in the field of epigenetics.

Keywords 3D chromatin structure, DNA methylation, histone modification, RNA modification, single-cell epigenomics

INTRODUCTION

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In 1942, Conrad Waddington defined “epigenetics” as a change in phenotype without a change in genotype (Waddington, 1942). Based on the current understanding from several studies, epigenetics is that the total DNA content in somatic cells is the same and there is no change in the existing DNA sequence, whereas the inheritance of gene expression patterns markedly varies among various cell types depending on changes in the chromatin state (Felsenfeld, 2014). Epigenetic mechanisms, in addition to DNA templates, can affect gene regulation during and after transcription and translation (Halušková, 2010). These properties can be profiled by various sequencing techniques. In addition, recent single-cell based profiling methods provide an opportunity to identify cell-to-cell variability. In this review, we provide a general overview of representative epigenetic phenomena, such as DNA methylation and histone modification, and epigenome profiling methods.

HISTONE MODIFICATIONS

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In eukaryotic cells, DNA is surrounded by chromatin in the nucleus (Jenuwein and Allis, 2001). Eukaryotic chromatin is a highly condensed that is structure essential for basic nuclear processes such as transcription and replication. Chromatin is divided into weakly and strongly condensed regions. The weakly condensed region is a region called euchromatin where transcription is generally active, shereas the strongly condensed region is a region called heterochromatin where gene expression is restricted (Back, 1976). The nucleosome is the basic unit of chromatin and consists of approximately 147 DNA base pairs and a histone octamer with two subunits H2A, H2B, H3, and H4 (Jenuwein and Allis, 2001). These histone tails of chromatin can be modified post-translationally by acetylation, methylation, and phosphorylation (Strahl and Allis, 2000) (Fig. 1). These post-translational covalent modifications are accumulated by epigenetic mechanisms and can alter the chromatin state and subsequent gene expression (Kouzarides, 2007) (Fig. 2). Histone modifications are mainly profiled using chromatin immunoprecipitation followed by sequencing (ChIP-seq) (Barski et al., 2007; Mikkelsen et al., 2007). In recent studies, histone modification information has been analyzed using Tn5 transposase-mediated tagmentation techniques such as cleavage under target and tagmentation (CUT&TAG) with few cells (Kaya-Okur et al., 2019) (Table 1).

Histone acetylation

Histone acetylation is the process by which the acetyl group of acetyl-CoA is transferred to the NH3+ group of the histone lysine. The addition of an acetyl group neutralizes the positive state of lysine and reduces the binding of histone proteins to DNA, making the DNA open and accessible to transcription factors (Bannister and Kouzarides, 2011). Histone hyperacetylation is a hallmark of transcriptional activity (Clayton et al., 1993; Pogo et al., 1966). The balance of histone acetyltransferases (HATs) and histone deacetylases (HDACs) is an important factor in the regulation of histone acetylation. HATs can be divided into two classes based on their subcellular localization and function (Parthun, 2007). A-type HATs are nuclear enzymes involved in the regulation of gene expression through the acetylation of nucleosomal histones in the chromatin context. B-type HATs are located in the cytoplasm and are responsible for acetylating newly synthesized histones prior to their transport from the cytoplasm to the nucleus where they assemble into nucleosomes (Roth et al., 2001) (Table 2).

HDACs oppose the effects of HATs and reverse lysine acetylation. In humans, there are four distinct classes of 18 HDACs: class I (Rpd3-like) (HDAC1-3 and HDAC8) and class II (Hda1-like) (HDAC4-7, HDAC9, and HDAC10), class III NAD-dependent enzymes of (Sir2-like) (SIRT1-7), and class IV for the single-member HDAC11 (Yang and Seto, 2008). In general, they are involved in multiple signaling pathways, and have relatively low specificity for particular acetyl groups, allowing a single enzyme to deacetylate multiple sites within histones. Various HDAC inhibitors have been developed and used to treat tumors. They can also induce cancer cell cycle arrest, differentiation, and apoptosis (Bose et al., 2014; Suraweera et al., 2018) (Table 2).

Histone phosphorylation

Phosphorylation is one of the most common post-translational modifications that occur on serine, threonine, and tyrosine residues of histone proteins (North et al., 2014). Similar to histone acetylation, this modification is highly dynamic and its levels are regulated by the addition and removal phosphate groups (Oki et al., 2007). Phosphoryl groups are transferred from ATP to the hydroxyl groups of amino acids by kinases, thereby adding a negative charge to histone proteins. In mammalian cells, H3S10 phosphorylation, which is mediated by Aurora -B kinase, is essential for mitosis and meiosis (Wei et al., 1998). This is because H3S10 phosphorylation dissociates the HP1 protein, which contributes to heterochromatin formation recruited by H3K9me3 in the interphase, from chromatin and prevents the formation of condensed heterochromatin. In addition, phosphorylation of the 139th serine group of H2AX is a histone modification induced by ATM and ATR. These modifications are involved in various DNA damage response pathways, including non-homologous end joining and homologous recombination (Cheung et al., 2005; Downs et al., 2004).

Histone methylation

Histone methylation usually occurs on the side chains of lysine and arginine and is one of the most important post-transcriptional modifications. Unlike acetylation and phosphorylation, histone methylation does not affect the charge on histone proteins. Histone lysine residues can be mono-, di-, or tri-methylated, while arginine residues can be mono- or di-methylated (Lan and Shi, 2009; Ng et al., 2009). Most histone lysine methyltransferases (HKMTs) have an evolutionarily well-conserved sequence motif identified in Drosophila called Su(var)3-9, Enhancer-of-zeste, and Trithorax (SET) (Schuhmacher et al., 2015; Spellmon et al., 2015).

H3K9 methylation is associated with heterochromatin. The methylation of H3K9 is driven by SUV39H1/2, G9a, G9a-like protein (GLP), and SETDB1 (Fritsch et al., 2010). SETDB1 co-translationally catalyzes mono- and dimethylation when H3K9 binds to ribosomes. G9a and GLP can form homomeric and heteromeric complexes and are involved in the formation of H3K9me1 and H3K9me2 (Tachibana et al., 2002). SUV39H1/2 is a key enzyme for H3K9me3 in the pericentromeric heterochromatin (Rea et al., 2000). H3K4 methylation is enriched in enhancer regions, promoter regions, and transcription start sites and is usually associated with the transcriptional activation of nearby genes. H3K4me1 and H3K4me3 are distributed in the enhancer and promoter regions, respectively, and H3K4me2 is distributed in the replication origin region and the 5’ end of genes (Heintzman et al., 2007; Kim and Buratowski, 2009; Santos-Rosa et al., 2002). Their distribution locations are related to their functions. Set1, a H3K4 methyltransferase identified in yeast, operates in COMPASS, a complex protein related to Set1 (Briggs et al., 2001; Miller et al., 2001). This enzyme is well conserved from yeast to humans and is responsible for H3K4 methylation. H3K27 methylation is induced by PRC2, a complex of polycomb group proteins. PRC2 has four core subunits (Ezh2, Suz12, EED, and RbAP46/48), and EZh2 catalyzes methylation (Cao et al., 2002; Kuzmichev et al., 2002). H3K27me2 and H3K27me3 are the hallmarks of gene repression (Banaszynski et al., 2013; Barski et al., 2007) (Fig. 2). Conversely, H3K27me1 is associated with transcriptional promotion and is distributed in the promoter regions of the active genes (Barski et al., 2007). H3K36 and H3K79 methylation are considered to be active markers distributed in actively transcribed chromatin regions. H3K36 can be mono- and demethylated by NSD1-3 and ASH1L, and trimethylation is catalyzed by SETD2 (Eram et al., 2014). H3K36 methylation can inhibit the activity of PRC2, preventing H3K27 methylation catalyzed by PRC2 (Yuan et al., 2011). In mammals, H3K79 is methylated by DOT1L. Unlike other HKMTs, DOT1L does not contain a SET domain because it is located in a globular histone core that is difficult for H3K79 to access (Jones et al., 2008) (Table 2).

Histone methylation in cancer

Aberrant histone modifications can affect chromosomal segregation or abnormal regulation of oncogenes and/or tumor suppressor genes (Table 2). Histone modification, which is frequently observed in cancer cells, is the loss of HDAC-mediated acetylation (Li and Seto, 2016). SIRT1 and deacetylase activities are upregulated in various tumor types. In addition to the loss of acetylation, gene silencing due to increased H3K27me3 due to EZH2 overexpression has been implicated in the progression of several solid malignancies, such as breast cancer (Kleer et al., 2003). Overexpression of lncRNA HOTAIR in ovarian cancer recruits EZH2 and alters the H3K27me3 landscape (Dai et al., 2021). It has also been reported that histone demethylase lysine-specific demethylase 4 A promotes the progression of nasopharyngeal carcinoma by promoting hypoxia-inducible factor-1α expression (Zhao et al., 2021). Aberrant histone modifications are closely related to cancer, and histone-modifying enzyme inhibitors such as HDAC inhibitors are being actively studied and developed.

DNA METHYLATION

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DNA methylation was first reported in 1948, and its role in gene regulation was first suggested in the mid-1970s (Holliday and Pugh, 1975; Hotchkiss, 1948). In mammalian DNA, there are many 5-methylcytosine (5mC) in sequences where cytosine and guanine are connected in the 5' to 3' direction (Coulondre et al., 1978). Most DNA methylations are stable and play important roles during development and the cell cycle in several epigenetic processes, such as genomic imprinting and X-chromosome inactivation (Smith and Meissner, 2013). DNA methylation plays an important role in controlling the epigenetic environment during reprogramming of somatic cells into pluripotent stem cells (Lee et al., 2014), which is mediated by DNA methyltransferase enzymes (DNMTs) (Table 2). 5mC is mainly profiled using whole-genome bisulfite sequencing (BS-seq) (Cokus et al., 2008). In addition, techniques such as reduced representation bisulfite sequencing (RRBS) and methylated DNA immunoprecipitation sequencing (MeDIP-seq) have been developed to profile the DNA methylation information (Meissner et al., 2005; Weber et al., 2005) (Table 1).

Location of DNA methylation

In the mammalian genome, CpG islands are DNA sequences approximately 1000 base pairs in length with a higher CpG density than the rest of the genome (Bird et al., 1985). Most gene promoters (more than 2/3), particularly promoters of housekeeping genes, are embedded in CpG islands (Saxonov et al., 2006). In general, CpG sites in promoter regions within CpG islands are not methylated differently from the other CpG sites (Bird et al., 1985). Silencing of gene expression by methylation of promoter DNA is stable and long-lasting, unlike transcriptional repression by histone modifications (Mohn et al., 2008). Because of these properties, methylation of CpG islands is an important epigenetic mechanism that regulates imprinted genes and gene expression during development and differentiation. Unlike promoter methylation, gene body DNA methylation is positively correlated with gene expression and is considered a characteristic of transcribed genes in cells (Ball et al., 2009). CpG islands within genes or gene bodies can reveal specific methylation differences between tissues or cancer samples. However, CpG islands in promoter regions show little difference in methylation and specific differences at some distance from the CpG islands (called CpG island shores) (Irizarry et al., 2009).

Writing and erasing DNA methylation

DNA methylation consists of three stages: de novo DNA methylation, maintenance, and demethylation (Fig. 3). DNMT3A and DNMT3B, known as de novo methyltransferases, consist of three main domains: the Pro-Trp-Trp-Pro (PWWP), ATRX-DNMT3-DNMT3L (ADD), and MTase domains (Okano et al., 1998; 1999). The ADD domain binds to the unmodified K4 residue of the H3 tail, until it binds to the MTase domain and acts as an inhibitor (Guo et al., 2015). When the ADD domain binds to unmodified H3K4, the ADD domain unbinds from the MTase domain and enables DNA methylation (Otani et al., 2009). As the ADD domain is repelled by the increasing number of methyl residues in H3K4, DNA methylation does not normally occur in CpG-rich promoters of H3K4me3 enriched genes (Piunti and Shilatifard, 2016). As transcription proceeds, the PWWP domain binds to H3K36me3 generated by the histone methyltransferase SETD2 to induce DNA methylation in the gene body (Dhayalan et al., 2010). Among de novo methylations, only symmetrical CpG methylation is maintained during DNA replication. This depends on the activity of DNMT1 and UHRF1, an E3 ubiquitin-protein ligase with five conserved domains (Arita et al., 2012). It works together with the TTD and PHD domains of UHRF1 to recognize and bind to H3K9me3, thereby loading DNMT1 onto the newly synthesized DNA substrate (Karg et al., 2017). Therefore, DNMT1 is located on the replication pork where newly synthesized hemimethylated DNA is formed during DNA replication (Leonhardt et al., 1992). DNMT1 is called maintenance DNMT because it maintains the pattern of DNA methylation. DNA methylation can be erased by passive or active demethylation. Passive demethylation leads to replication-dependent dilution of 5mC due to defects in the maintenance methylation mechanism that copies methylation patterns during DNA replication (Howell et al., 2001). Passive demethylation is biologically important for erasing DNA methylation in preimplantation embryos and primordial germ cells. Active DNA demethylation mechanisms have been found to be mediated by Tet1, Tet2, and Tet3 enzymes. The TET protein oxidizes 5mC to produce 5-hydroxymethylcytosine (5hmC) and undergoes demethylation (Ito et al., 2010; Tahiliani et al., 2009). 5hmC can be further oxidized to generate 5fC and 5caC, which can be removed and converted to an unmethylated cytosine by the DNA glycosylase (TDG and SMUG1) and base excision repair pathways, respectively (Maiti and Drohat, 2011; Weber et al., 2016) (Table 2).

DNA methylation crosstalk

DNA methylation and histone modification work together to regulate transcription. Because DNMTs generally suppress gene regions through methylation, they inhibit gene expression by interacting with enzymes that regulate histone modification. DNMT1 and DNMT3a restrict gene expression by binding to SUV39H1, an enzyme that methylates H3K9 (Fuks et al., 2000). In addition, DNMT1 and DNMT3b bind to HDACs and regulate gene expression (Fuks et al., 2000; Geiman et al., 2004). Methyl-binding proteins, such as MeCP2 and UHRF, enhance gene repression by interacting with methylated DNA and histones (Nan et al., 1998). Although the interaction between RNA and DNA modifications is not clearly defined, recent studies have reported that high N6-methyl adenosine (m6A) modifications in esophageal squamous cell carcinoma cells lead to DNA demethylation, altering chromatin accessibility and affecting gene transcription (Deng et al., 2022).

DNA methylation in multiple diseases

DNA methylation is involved in various diseases such as brain disorders and cancer (Table 2). For example, an autosomal-dominant mutation in the N-terminal regulatory domain of DNMT1 was identified in patients with hereditary sensory and autonomic neuropathy type 1, who presented with dementia, hearing loss, and narcolepsy in adulthood (Klein et al., 2011). DNMT3A is associated with the development of acute myeloid leukemia (AML), and TET2 mutations are considered a common epigenetic marker in several hematological malignancies including AML, chronic myelomonocytic leukemia, and lymphomas {Langemeijer, 2009, Acquired mutations in TET2 are common in myelodysplastic syndromes}(Langemeijer et al., 2009; Spencer et al., 2017). Overexpression of UHRF1 promotes hypermethylation of the promoter of thioredoxin-interacting protein (TXNIP), a tumor suppressor gene, and downregulates TXNIP expression in cervical cancer, contributing to carcinogenesis (Kim et al., 2021). The DNMT3A mutation is a missense mutation of Arginine 882 (R882) in the MTase domain, which interferes with DNMT3A formation and reduces the methylation activity of the enzyme (Russler-Germain et al., 2014). Conversely, TET2 mutations induce hypermethylation of enhancer regions in myeloid malignancies (Ko et al., 2010). It is still unclear how two mutants with opposite functions can achieve similar phenotypes. A recent study on patients with AML demonstrated that mutations in DNMT3A and TET2 can cause irregular DNA methylation patterns and transcriptional expression levels in genes known to be involved in AML pathogenesis (Ponciano-Gómez et al., 2017). In addition, Lee et al. (2023) reported that the regulation of C-Maf-inducing protein methylation mediated by DNMT1 and TET2 was correlated with nonalcoholic fatty liver disease.

CHROMATIN CONFORMATION

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In mammalian cells, DNA forms nucleosomes, which are arranged into higher-order chromatin structures that play important roles in regulating the cell cycle, replication, development and gene function. The three-dimensional chromatin structure includes cis-regulatory interactions such as enhancer-promoter interactions and repressive interactions such as lamina-associated domains (LADs) and is mediated by structural elements such as CCCTC-binding factor (CTCF) and cohesin (Huang et al., 2021; Rowley and Corces, 2018; Schoenfelder and Fraser, 2019).

Enhancers, a representative cis-regulatory element, are usually several kilobases different from gene promoters but can be involved in transcriptional regulation through reduced spatial proximity to promoters by forming chromatin looping and folding. Chromatin conformation capture (3C) profiles the interactions between these specific genomic regions (Dekker et al., 2002). A recent technique, Hi-C, allows global quantification of all interactions present in the nucleus. Based on the Hi-C data, it was possible to analyze compartments, which are sets of chromosomal regions with similar, long-range Hi-C contact patterns and self-interacting genomic regions called topologically associated domains (TADs) (Dixon et al., 2012; Lieberman-Aiden et al., 2009). Compartment A is associated with open chromatin, and Compartment B is associated with closed chromatin and is specific to the cell type (Dixon et al., 2012). Previous studies have reported that TADs are well conserved among various cell types and species. However, multiple methods based on Hi-C have been developed at the single-cell level, and recent studies have shown that chromatin contacts, such as TAD structures, vary considerably at the single-cell level (Stevens et al., 2017). In general, the frequency of interactions within TADs is high and the interaction between TADs is generally low. CTCF is an important factor in regulating TAD structure and is involved in the insulation between TADs (Szabo et al., 2020). The disruption of TAD boundaries can affect gene expression and is associated with various diseases and cancers. A recent study reported that the combination of genome profiling and CRISPR-Cas9 genome engineering could identify regions with repetitive changes in the 3D genome structure and predict oncogene activity (Xu et al., 2022). Nuclear lamina and constituent filament proteins, A/B type lamins, are located in the nuclear envelope. LADs are heterochromatic regions that constitute approximately 40% of the genome and are in contact with the nuclear lamina. The LAD region is enriched in H3K9me2/3 and H3K27me3, and a few genes within the LAD are expressed (Guelen et al., 2008; Lund et al., 2014).

RNA MODIFICATION

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Mammalian RNA undergoes numerous post-transcriptional chemical modifications. Although these RNA modifications were discovered in the 1970s, their importance has not yet been highlighted. Over the past decade, several studies have shown that RNA modifications play an important role in regulating gene expression, similar to the epigenetic modifications of DNA and histones (Helm and Motorin, 2017).

m6A is the most abundant endogenous RNA modification in eukaryotes. m6A is precisely controlled by three protein groups: “writers” that install m6A residues along target RNA transcripts, “erasers” that remove modifications at specific sites, and “readers” that recognize modified regions. m6A RNA methylation is catalyzed by “writer” proteins, m6A methyltransferase-like 3 and 14 (METTL3 and METTL14). METTL3 and METTL14 form stable heterodimer complexes (Bokar et al., 1997; Liu et al., 2014). In addition, the METTL3-METTL14 complex interacts with Wilms tumor 1-associated protein to target a wide range of RNA substrates and install m6A (Ping et al., 2014). m6A demethylation is catalyzed by the AlkB family of non-heme Fe(II)/α-KG-dependent dioxygenases. Representative major human AlkB family members include fat mass- and obesity-associated protein (FTO) and alkylation repair homolog protein 5 (ALKBH5). FTO is an RNA demethylase first discovered in mammalian cells that removes m6A by generating N6-hydroxymethyladenosine and N6-formyladenosine, which can be hydrolyzed into adenine through continuous oxidation over several hours (Fu et al., 2013). ALKBH5 catalyzes the m6A-to-A conversion by directly removing the methyl group (Jang et al., 2022; Zheng et al., 2013). The YT521-B homology (YTH) domain-containing protein family recognizes and binds to m6A. YTHDC1 is located in the nucleus and is characterized by various RNA splicing regulators, such as serine-arginine repeat proteins. It recognizes m6A on the lncRNA XIST and mediates X chromosome silencing (Patil et al., 2016; Zhang et al., 2010). YTHDF1 and YTHDF3 regulate translation efficiency by interacting with the ribosome of the target RNA, and YTHDF2 promotes the degradation of m6A-modified RNA by recruiting deadenylation enzyme complexes, thereby affecting RNA stability (Du et al., 2016; Li et al., 2017; Wang et al., 2015).

m6A modification is associated with various diseases and cancers. METTL3 promotes the maturation of mir-1246 by methylating pri-mir-1246 and down-regulating the anti-oncogene SPRED2, thereby improving the tumor metastasis ability of colorectal cancer (Peng et al., 2019). In addition, METTL3 is also associated with prostatitis and Aicardi syndrome, FTO is an oncogene in AML, breast cancer and colorectal cancer, and YTHDF1 and YTHDF2 are associated with pancreatic cancer and breast cancer, respectively (Huang et al., 2019; Liu and Pan, 2015; Pan et al., 2021).

SINGLE-CELL EPIGENOMIC PROFILING TECHNIQUES

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Several techniques have been developed to profile epigenetic regulation (Table 1). However, although these bulk-cell profiling methods showed an average signal for a cell population, it was difficult to represent cell-to-cell variation within tissue, such as gene expression heterogeneity. Single-cell epigenomic analysis has the potential to overcome these limitations and to elucidate gene regulatory mechanisms across diverse cellular environments.

Single-cell ChIP-seq (scChIP-seq) was the first reported technique for profiling histone modifications at the single-cell level. scChIp-seq separates single cells into droplets containing lysis buffer and micrococcal nuclease (MNase), followed by barcoding before immunoprecipitation (Rotem et al., 2015). Since then, several technologies have been developed, such as single-cell chromatin immunocleavage followed by sequencing, chromatin integration labeling sequencing, single-cell cleavage under targets and release using nucleases (scCUT&RUN), and CUT&TAG (Bartosovic et al., 2021; Harada et al., 2019; Kaya-Okur et al., 2019; Ku et al., 2019). Several single-cell studies have confirmed that cell-to-cell variations in histone modifications are correlated with heterogeneity in gene expression. For example, measurements of H3K4me2 levels within mouse embryonic stem cell populations revealed significant variation, which was observed in gene enhancers and transcriptionally repressed genes (Rotem et al., 2015). In addition, integrating single-cell-level H3K4me3 profiling and scRNA-seq in the mouse brain confirmed cellular heterogeneity in oligodendrocyte populations, which appeared homogenous and revealed that they could be dispersed into subpopulations enriched with module-specific genes (Bartosovic et al., 2021).

Single-cell level profiling of DNA methylation has mainly been achieved through bisulfite conversion methods such as single-cell BS-seq (scBS-seq), single-cell RRBS, and post-bisulfite adapter-tagging (Guo et al., 2013; Miura et al., 2012; Smallwood et al., 2014). Bisulfite sequencing is based on the conversion of unmethylated cytosine into uracil. scRRBS generates DNA fragments containing CpG-rich ends by using one or more restriction enzymes, followed by bisulfite sequencing (Guo et al., 2013). scBS-seq was used to perform bisulfite treatment and random priming and extension after cell isolation and lysis (Smallwood et al., 2014). These methods show heterogeneity in DNA methylation in both mouse and human cells. Multi-omics techniques have also been developed to investigate the interaction between DNA methylation heterogeneity, gene expression heterogeneity and other epigenetic data (Table 3). For example, single-cell methylome and transcriptome sequencing (scM&T-seq) have demonstrated a functional link between transcriptional and DNA methylation heterogeneity of gene promoters within specific cell and tissue types in mouse muscle stem cells (Angermueller et al., 2016).

Chromatin accessibility plays an important role in the regulation of gene expression by influencing transcription initiation. Chromatin accessibility can be profiled by assays for transposase-accessible chromatin sequencing (ATAC-seq) and DNase I hypersensitive site sequencing (DNase-seq). These methods measure chromatin accessibility based on enzymatic sensitivity (Buenrostro et al., 2013; Song and Crawford, 2010). Single-cell ATAC-seq (scATAC-seq) and single-cell DNase-seq, similar to other single-cell epigenetic profiling techniques, can identify heterogeneity between cells using the chromatin approach. Cusanovich et al. (2015) appliedcombinatorial indexing to intact nuclei and were able to distinguish between various cell types by profiling thousands of cells. In addition, a recent study performed scATAC-seq and scRNA-seq on DNA and mRNA of the same cell, respectively, and found a positive correlation between gene expression and chromatin accessibility heterogeneity in each cell (Reyes et al., 2019).

Research on 3D genome structure has been greatly improved by bulk cell Hi-C, but cell-to-cell variability of 3D genome features such as TADs or enhancer-promoter contacts could not be accurately reflected. Single-cell Hi-C can be used to perform interaction profiling depending on the proximity ligation region. These techniques based on Hi-C have revealed that chromatin contact varies depending on cell type and developmental status. Using single-cell Hi-C, Nagano et al. (2017) found that mouse embryonic stem cells showed chromosomal condensation in the early G1 phase and extensive reorganization during replication, suggesting that the cell cycle is related to heterogeneity in chromatin contact. In addition, single-nucleus Hi-C removed the previously used biotin-filling step and performed sticky end ligation, revealing that the chromatin structure was uniquely reconstructed during the oocyte-to-zygote transition in mice (Flyamer et al., 2017) (Fig. 4).

Recently, multi-modal omics techniques that can simultaneously profile two or more epigenetic features in a single cell have facilitated the analysis of the correlations between different traits. For example, sn-m3C-seq can simultaneously profile DNA methylation and chromatin conformation at a single-cell level (Lee et al., 2019). In addition, Paired-seq and SNARE-seq can simultaneously profile gene expression and chromatin accessibility information, as well as scM&T-seq and snmC2T-seq can co-profile transcriptome and methylome information (Angermueller et al., 2016; Chen et al., 2019; Luo et al., 2022; Zhu et al., 2019). Many multi-modal omics techniques are still being developed, which will further advance our biological understanding (Table 3).

CONCLUSION

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In this review, several characteristics such as DNA methylation and histone modification, which are representative of epigenetic characteristics, were summarized. Mostly, epigenetics focus on molecular biology approaches. However, even if it is not genetic, DNA or histone modifications and three-dimensional chromatin structure have a great influence on the changes that can occur within individual cells. Since the 1980s, scientific interest in the molecular mechanisms of epigenetic control to understand disease development and treatment has continued to grow. Despite numerous studies, several epigenetic mechanisms and patterns remain unknown. However, by integrating advanced techniques sophisticated algorithms, it is now possible to generate and analyze large volumes of epigenetic data. Single-cell multi-omics-based sequencing techniques that are being actively studied can generate information on two or more epigenetic traits. These epigenetic data can facilitate correlation analysis between different traits. Advances in these technologies and information will provide opportunities to establish novel epigenetic markers and their functions in different types of tissue, development, and disease states.

FIGURES

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Fig. 1. Overview of epigenomic features and single cell profiling techniques. sc, single-cell; sn, single-nucleus; Hi-C, high-throughput chromosome conformation capture; ChIP-seq, chromatin immunoprecipitation followed by sequencing; ChIC-seq, chromatin immunocleavage followed by sequencing; ChIL-seq, chromatin integration labelling sequencing; CUT&RUN, cleavage under targets and release using nucleasee; CUT&TAG, cleavage under targets and tagmentation; ATAC-seq, assay for transposase-accessible chromatin sequencing; DNase-seq, DNase I hypersensitive site sequencing; MNase-seq, micrococcal nuclease sequencing; RRBS, reduced representation bisulfite sequencing; BS-seq, bisulfite sequencing; PBAT, post-bisulfite adapter-tagging; 5mC, 5-methylcytosine; 5hmC, 5-hydroxymethylcytosine; 5fC, 5-fluorocytosine.
Fig. 2. Gene regulation of histone modifications.
Fig. 3. DNA methylation and modifying enzymes.
Fig. 4. Single-cell epigenome profiling techniques.

TABLES

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Table 1.

Methods for profiling epigenetic traits

Data typeMethodsReference
Histone modificationChIP-seq(Barski et al., 2007)
CUT&TAG(Kaya-Okur et al., 2019)
CUT&RUN(Skene and Henikoff, 2017)
DNA methylationBS-seq(Cokus et al., 2008)
RRBS(Meissner et al., 2005)
MeDIP-seq(Weber et al., 2005)
Chromatin contactHi-C(Lieberman-Aiden et al., 2009)
ChIA-PET(Wei et al., 2006)
Hi-ChIP(Mumbach et al., 2016)

Table 2.

Epigenetic changes and associated proteins

Epigenetic modificationAssociated proteinFunctionReference
Maintenance DNA methylationDNMT1Maintain the pattern of DNA methylation(Klein et al., 2011)
De novo DNA methylationDNMT3A, DNMT3BMethylation of unmodified DNA(Spencer et al., 2017)
DNA demethylationTET1, TET2, TET3Remove methylation(Ponciano-Gómez et al., 2017)
Histone acteylationp300/CBPTranscription activation(Benton et al., 2017)
Histone deacetylationHDACsTranscriptional regulation(Li and Seto, 2016)
H3K4 methylationSET1Transcription activation(Zaidi et al., 2013)
H3K9 methylationEZH2, G9a/GLPTranscription repression(Iacono et al., 2018)
H3K27 methylationPRC2Transcription repression (H3K27me1 is associated with transcription activiation)(Huang et al., 2021)
H3K79 methylationDOT1LTranscription activation(Johnson et al., 2009)
RNA methylationMETTL3, METTL14, WTAPInstallation of m6A on RNA residue(Ma et al., 2017)
YTHDF1/2/3, YTHDC1Binding with m6A(Paris et al., 2019)
RNA demethylationFTO, ALKBH5Remove of m6A on RNA residue(Zhang et al., 2016)

Table 3.

Multimodal omics techniques

MethodsProfiling featuresReference
DR-seqGenome, transcriptome(Dey et al., 2015)
G&T-seqGenome, transcriptome(Macaulay et al., 2015)
scTrio-seqGenome, transcriptome(Hou et al., 2016)
SIDR-seqGenome, transcriptome(Han et al., 2018)
CORTAD-seqGenome, transcriptome(Kong et al., 2019)
TARGET-seqGenome, transcriptome(Rodriguez-Meira et al., 2019)
PEA/STATranscriptome, proteome(Genshaft et al., 2016)
PLAYRTranscriptome, proteome(Frei et al., 2016)
AbseqTranscriptome, proteome(Shahi et al., 2017)
CITE-seqTranscriptome, proteome(Stoeckius et al., 2017)
REAP-seqTranscriptome, proteome(Peterson et al., 2017)
RAIDTranscriptome, proteome(Gerlach et al., 2019)
ECCITE-seqTranscriptome, proteome(Mimitou et al., 2019)
sci-CARChromatin accessibility, transcriptome(Cao et al., 2018)
T-ATAC-seqChromatin accessibility, transcriptome(Satpathy et al., 2018)
scCAT-seqChromatin accessibility, transcriptome(Liu et al., 2019)
SNARE-seqChromatin accessibility, transcriptome(Chen et al., 2019)
ATAC-RNA-seqChromatin accessibility, transcriptome(Reyes et al., 2019)
Paired-seqChromatin accessibility, transcriptome(Zhu et al., 2019)
scMT-seqDNA methylome, transcriptome(Hu et al., 2016)
scM&T-seqDNA methylome, transcriptome(Angermueller et al., 2016)
sc-GEMDNA metyhlome, transcriptome(Cheow et al., 2016)
scNMT-seqChromatin accessibility, DNA methylome, transcriptome(Clark et al., 2018)
scChaRM-seqChromatin accessibility, DNA methylome, transcriptome(Yan et al., 2021)
scNOMeRe-seqChromatin accessibility, DNA methylome, transcriptome(Wang et al., 2021)
snmCAT-seqChromatin accessibility, DNA methylome, transcriptome(Luo et al., 2022)
DART-seqTranscriptome, RNA methylome(Meyer, 2019)
ORCATranscriptome, chromatin conformation(Mateo et al., 2019)

REFERENCES

Go to
  1. Angermueller C., Clark S.J., Lee H.J., Macaulay I.C., Teng M.J., Hu T.X., Krueger F., Smallwood S.A., Ponting C.P., and Voet T. (2016). Parallel single-cell sequencing links transcriptional and epigenetic heterogeneity. Nat. Methods 13, 229-232.
    Pubmed KoreaMed CrossRef
  2. Arita K., Isogai S., Oda T., Unoki M., Sugita K., Sekiyama N., Kuwata K., Hamamoto R., Tochio H., and Sato M. (2012). Recognition of modification status on a histone H3 tail by linked histone reader modules of the epigenetic regulator UHRF1. Proc. Natl. Acad. Sci. U. S. A. 109, 12950-12955.
    Pubmed KoreaMed CrossRef
  3. Back F. (1976). The variable condition of euchromatin and heterochromatin. Int. Rev. Cytol. 45, 25-64.
    Pubmed CrossRef
  4. Ball M.P., Li J.B., Gao Y., Lee J.H., LeProust E.M., Park I.H., Xie B., Daley G.Q., and Church G.M. (2009). Targeted and genome-scale strategies reveal gene-body methylation signatures in human cells. Nat. Biotechnol. 27, 361-368.
    Pubmed KoreaMed CrossRef
  5. Banaszynski L.A., Wen D., Dewell S., Whitcomb S.J., Lin M., Diaz N., Elsässer S.J., Chapgier A., Goldberg A.D., and Canaani E. (2013). Hira-dependent histone H3. 3 deposition facilitates PRC2 recruitment at developmental loci in ES cells. Cell 155, 107-120.
    Pubmed KoreaMed CrossRef
  6. Bannister A.J. and Kouzarides T. (2011). Regulation of chromatin by histone modifications. Cell Res. 21, 381-395.
    Pubmed KoreaMed CrossRef
  7. Barski A., Cuddapah S., Cui K., Roh T.Y., Schones D.E., Wang Z., Wei G., Chepelev I., and Zhao K. (2007). High-resolution profiling of histone methylations in the human genome. Cell 129, 823-837.
    Pubmed CrossRef
  8. Bartosovic M., Kabbe M., and Castelo-Branco G. (2021). Single-cell CUT&Tag profiles histone modifications and transcription factors in complex tissues. Nat. Biotechnol. 39, 825-835.
    Pubmed KoreaMed CrossRef
  9. Benton C.B., Fiskus W., and Bhalla K.N. (2017). Targeting histone acetylation: readers and writers in leukemia and cancer. Cancer J. 23, 286-291.
    Pubmed CrossRef
  10. Bird A., Taggart M., Frommer M., Miller O.J., and Macleod D. (1985). A fraction of the mouse genome that is derived from islands of nonmethylated, CpG-rich DNA. Cell 40, 91-99.
    Pubmed CrossRef
  11. Bokar J.A., Shambaugh M.E., Polayes D., Matera A.G., and Rottman F.M. (1997). Purification and cDNA cloning of the AdoMet-binding subunit of the human mRNA (N6-adenosine)-methyltransferase. RNA 3, 1233-1247.
    Pubmed KoreaMed
  12. Bose P., Dai Y., and Grant S. (2014). Histone deacetylase inhibitor (HDACI) mechanisms of action: emerging insights. Pharmacol. Ther. 143, 323-336.
    Pubmed KoreaMed CrossRef
  13. Briggs S.D., Bryk M., Strahl B.D., Cheung W.L., Davie J.K., Dent S.Y., Winston F., and Allis C.D. (2001). Histone H3 lysine 4 methylation is mediated by Set1 and required for cell growth and rDNA silencing in Saccharomyces cerevisiae. Genes Dev. 15, 3286-3295.
    Pubmed KoreaMed CrossRef
  14. Buenrostro J.D., Giresi P.G., Zaba L.C., Chang H.Y., and Greenleaf W.J. (2013). Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, DNA-binding proteins and nucleosome position. Nat. Methods 10, 1213-1218.
    Pubmed KoreaMed CrossRef
  15. Cao J., Cusanovich D.A., Ramani V., Aghamirzaie D., Pliner H.A., Hill A.J., Daza R.M., McFaline-Figueroa J.L., Packer J.S., and Christiansen L. (2018). Joint profiling of chromatin accessibility and gene expression in thousands of single cells. Science 361, 1380-1385.
    Pubmed KoreaMed CrossRef
  16. Cao R., Wang L., Wang H., Xia L., Erdjument-Bromage H., Tempst P., Jones R.S., and Zhang Y. (2002). Role of histone H3 lysine 27 methylation in Polycomb-group silencing. Science 298, 1039-1043.
    Pubmed CrossRef
  17. Chen S., Lake B.B., and Zhang K. (2019). High-throughput sequencing of the transcriptome and chromatin accessibility in the same cell. Nat. Biotechnol. 37, 1452-1457.
    Pubmed KoreaMed CrossRef
  18. Cheow L.F., Courtois E.T., Tan Y., Viswanathan R., Xing Q., Tan R.Z., Tan D.S., Robson P., Loh Y.H., and Quake S.R. (2016). Single-cell multimodal profiling reveals cellular epigenetic heterogeneity. Nat. Methods 13, 833-836.
    Pubmed CrossRef
  19. Cheung W.L., Turner F.B., Krishnamoorthy T., Wolner B., Ahn S.H., Foley M., Dorsey J.A., Peterson C.L., Berger S.L., and Allis C.D. (2005). Phosphorylation of histone H4 serine 1 during DNA damage requires casein kinase II in S. cerevisiae. Curr. Biol. 15, 656-660.
    Pubmed CrossRef
  20. Clark S.J., Argelaguet R., Kapourani C.A., Stubbs T.M., Lee H.J., Alda-Catalinas C., Krueger F., Sanguinetti G., Kelsey G., and Marioni J.C. (2018). scNMT-seq enables joint profiling of chromatin accessibility DNA methylation and transcription in single cells. Nat. Commun. 9, 781.
    Pubmed KoreaMed CrossRef
  21. Clayton A.L., Hebbes T.R., Thorne A.W., and Crane-Robinson C. (1993). Histone acetylation and gene induction in human cells. FEBS Lett. 336, 23-26.
    Pubmed CrossRef
  22. Cokus S.J., Feng S., Zhang X., Chen Z., Merriman B., Haudenschild C.D., Pradhan S., Nelson S.F., Pellegrini M., and Jacobsen S.E. (2008). Shotgun bisulphite sequencing of the Arabidopsis genome reveals DNA methylation patterning. Nature 452, 215-219.
    Pubmed KoreaMed CrossRef
  23. Coulondre C., Miller J.H., Farabaugh P.J., and Gilbert W. (1978). Molecular basis of base substitution hotspots in Escherichia coli. Nature 274, 775-780.
    Pubmed CrossRef
  24. Cusanovich D.A., Daza R., Adey A., Pliner H.A., Christiansen L., Gunderson K.L., Steemers F.J., Trapnell C., and Shendure J. (2015). Multiplex single-cell profiling of chromatin accessibility by combinatorial cellular indexing. Science 348, 910-914.
    Pubmed KoreaMed CrossRef
  25. Dai Z.Y., Jin S.M., Luo H.Q., Leng H.L., and Fang J.D. (2021). LncRNA HOTAIR regulates anoikis-resistance capacity and spheroid formation of ovarian cancer cells by recruiting EZH2 and influencing H3K27 methylation. Neoplasma 68, 509-518.
    Pubmed CrossRef
  26. Dekker J., Rippe K., Dekker M., and Kleckner N. (2002). Capturing chromosome conformation. Science 295, 1306-1311.
    Pubmed CrossRef
  27. Deng S., Zhang J., Su J., Zuo Z., Zeng L., Liu K., Zheng Y., Huang X., Bai R., and Zhuang L. (2022). RNA m6A regulates transcription via DNA demethylation and chromatin accessibility. Nat. Genet. 54, 1427-1437.
    Pubmed CrossRef
  28. Dey S.S., Kester L., Spanjaard B., Bienko M., and Van Oudenaarden A. (2015). Integrated genome and transcriptome sequencing of the same cell. Nat. Biotechnol. 33, 285-289.
    Pubmed KoreaMed CrossRef
  29. Dhayalan A., Rajavelu A., Rathert P., Tamas R., Jurkowska R.Z., Ragozin S., and Jeltsch A. (2010). The Dnmt3a PWWP domain reads histone 3 lysine 36 trimethylation and guides DNA methylation. J. Biol. Chem. 285, 26114-26120.
    Pubmed KoreaMed CrossRef
  30. Dixon J.R., Selvaraj S., Yue F., Kim A., Li Y., Shen Y., Hu M., Liu J.S., and Ren B. (2012). Topological domains in mammalian genomes identified by analysis of chromatin interactions. Nature 485, 376-380.
    Pubmed KoreaMed CrossRef
  31. Downs J.A., Allard S., Jobin-Robitaille O., Javaheri A., Auger A., Bouchard N., Kron S.J., Jackson S.P., and Côté J. (2004). Binding of chromatin-modifying activities to phosphorylated histone H2A at DNA damage sites. Mol. Cell 16, 979-990.
    Pubmed CrossRef
  32. Du H., Zhao Y., He J., Zhang Y., Xi H., Liu M., Ma J., and Wu L. (2016). YTHDF2 destabilizes m6A-containing RNA through direct recruitment of the CCR4-NOT deadenylase complex. Nat. Commun. 7, 12626.
    Pubmed KoreaMed CrossRef
  33. Eram M.S., Bustos S.P., Lima-Fernandes E., Siarheyeva A., Senisterra G., Hajian T., Chau I., Duan S., Wu H., and Dombrovski L. (2014). Trimethylation of histone H3 lysine 36 by human methyltransferase PRDM9 protein. J. Biol. Chem. 289, 12177-12188.
    Pubmed KoreaMed CrossRef
  34. Felsenfeld G. (2014). A brief history of epigenetics. Cold Spring Harb. Perspect. Biol. 6, a018200.
    Pubmed KoreaMed CrossRef
  35. Flyamer I.M., Gassler J., Imakaev M., Brandão H.B., Ulianov S.V., Abdennur N., Razin S.V., Mirny L.A., and Tachibana-Konwalski K. (2017). Single-nucleus Hi-C reveals unique chromatin reorganization at oocyte-to-zygote transition. Nature 544, 110-114.
    Pubmed KoreaMed CrossRef
  36. Frei A.P., Bava F.A., Zunder E.R., Hsieh E.W., Chen S.Y., Nolan G.P., and Gherardini P.F. (2016). Highly multiplexed simultaneous detection of RNAs and proteins in single cells. Nat. Methods 13, 269-275.
    Pubmed KoreaMed CrossRef
  37. Fritsch L., Robin P., Mathieu J.R., Souidi M., Hinaux H., Rougeulle C., Harel-Bellan A., Ameyar-Zazoua M., and Ait-Si-Ali S. (2010). A subset of the histone H3 lysine 9 methyltransferases Suv39h1, G9a, GLP, and SETDB1 participate in a multimeric complex. Mol. Cell 37, 46-56.
    Pubmed CrossRef
  38. Fu Y., Jia G., Pang X., Wang R.N., Wang X., Li C.J., Smemo S., Dai Q., Bailey K.A., and Nobrega M.A. (2013). FTO-mediated formation of N6-hydroxymethyladenosine and N6-formyladenosine in mammalian RNA. Nat. Commun. 4, 1798.
    Pubmed KoreaMed CrossRef
  39. Fuks F., Burgers W.A., Brehm A., Hughes-Davies L., and Kouzarides T. (2000). DNA methyltransferase Dnmt1 associates with histone deacetylase activity. Nat. Genet. 24, 88-91.
    Pubmed CrossRef
  40. Geiman T.M., Sankpal U.T., Robertson A.K., Zhao Y., Zhao Y., and Robertson K.D. (2004). DNMT3B interacts with hSNF2H chromatin remodeling enzyme, HDACs 1 and 2, and components of the histone methylation system. Biochem. Biophys. Res. Commun. 318, 544-555.
    Pubmed CrossRef
  41. Genshaft A.S., Li S., Gallant C.J., Darmanis S., Prakadan S.M., Ziegler C.G., Lundberg M., Fredriksson S., Hong J., and Regev A. (2016). Multiplexed, targeted profiling of single-cell proteomes and transcriptomes in a single reaction. Genome Biol. 17, 188.
    Pubmed KoreaMed CrossRef
  42. Gerlach J., van Buggenum J.A., Tanis S.E., Hogeweg M., Heuts B.M., Muraro M.J., Elze L., Rivello F., Rakszewska A., and van Oudenaarden A. (2019). Combined quantification of intracellular (phospho-) proteins and transcriptomics from fixed single cells. Sci. Rep. 9, 1469.
    Pubmed KoreaMed CrossRef
  43. Guelen L., Pagie L., Brasset E., Meuleman W., Faza M.B., Talhout W., Eussen B.H., De Klein A., Wessels L., and De Laat W. (2008). Domain organization of human chromosomes revealed by mapping of nuclear lamina interactions. Nature 453, 948-951.
    Pubmed CrossRef
  44. Guo H., Zhu P., Wu X., Li X., Wen L., and Tang F. (2013). Single-cell methylome landscapes of mouse embryonic stem cells and early embryos analyzed using reduced representation bisulfite sequencing. Genome Res. 23, 2126-2135.
    Pubmed KoreaMed CrossRef
  45. Guo X., Wang L., Li J., Ding Z., Xiao J., Yin X., He S., Shi P., Dong L., and Li G. (2015). Structural insight into autoinhibition and histone H3-induced activation of DNMT3A. Nature 517, 640-644.
    Pubmed CrossRef
  46. Halušková J. (2010). Epigenetic studies in human diseases. Folia Biol. (Praha) 56, 83-96.
    Pubmed
  47. Han K.Y., Kim K.T., Joung J.G., Son D.S., Kim Y.J., Jo A., Jeon H.J., Moon H.S., Yoo C.E., and Chung W. (2018). SIDR: simultaneous isolation and parallel sequencing of genomic DNA and total RNA from single cells. Genome Res. 28, 75-87.
    Pubmed KoreaMed CrossRef
  48. Harada A., Maehara K., Handa T., Arimura Y., Nogami J., Hayashi-Takanaka Y., Shirahige K., Kurumizaka H., Kimura H., and Ohkawa Y. (2019). A chromatin integration labelling method enables epigenomic profiling with lower input. Nat. Cell Biol. 21, 287-296.
    Pubmed CrossRef
  49. Heintzman N.D., Stuart R.K., Hon G., Fu Y., Ching C.W., Hawkins R.D., Barrera L.O., Van Calcar S., Qu C., and Ching K.A. (2007). Distinct and predictive chromatin signatures of transcriptional promoters and enhancers in the human genome. Nat. Genet. 39, 311-318.
    Pubmed CrossRef
  50. Helm M. and Motorin Y. (2017). Detecting RNA modifications in the epitranscriptome: predict and validate. Nat. Rev. Genet. 18, 275-291.
    Pubmed CrossRef
  51. Holliday R. and Pugh J.E. (1975). DNA modification mechanisms and gene activity during development: developmental clocks may depend on the enzymic modification of specific bases in repeated DNA sequences. Science 187, 226-232.
    CrossRef
  52. Hotchkiss R.D. (1948). The quantitative separation of purines, pyrimidines, an d nucleosides by paper chromatography. J. Biol. Chem. 175, 315-332.
    Pubmed CrossRef
  53. Hou Y., Guo H., Cao C., Li X., Hu B., Zhu P., Wu X., Wen L., Tang F., and Huang Y. (2016). Single-cell triple omics sequencing reveals genetic, epigenetic, and transcriptomic heterogeneity in hepatocellular carcinomas. Cell Res. 26, 304-319.
    Pubmed KoreaMed CrossRef
  54. Howell C.Y., Bestor T.H., Ding F., Latham K.E., Mertineit C., Trasler J.M., and Chaillet J.R. (2001). Genomic imprinting disrupted by a maternal effect mutation in the Dnmt1 gene. Cell 104, 829-838.
    Pubmed CrossRef
  55. Hu Y., Huang K., An Q., Du G., Hu G., Xue J., Zhu X., Wang C.Y., Xue Z., and Fan G. (2016). Simultaneous profiling of transcriptome and DNA methylome from a single cell. Genome Biol. 17, 88.
    Pubmed KoreaMed CrossRef
  56. Huang H., Zhu Q., Jussila A., Han Y., Bintu B., Kern C., Conte M., Zhang Y., Bianco S., and Chiariello A.M. (2021). CTCF mediates dosage-and sequence-context-dependent transcriptional insulation by forming local chromatin domains. Nat. Genet. 53, 1064-1074.
    Pubmed KoreaMed CrossRef
  57. Huang Y., Su R., Sheng Y., Dong L., Dong Z., Xu H., Ni T., Zhang Z.S., Zhang T., and Li C. (2019). Small-molecule targeting of oncogenic FTO demethylase in acute myeloid leukemia. Cancer Cell 35, 677-691.e10.
    Pubmed KoreaMed CrossRef
  58. Iacono G., Dubos A., Méziane H., Benevento M., Habibi E., Mandoli A., Riet F., Selloum M., Feil R., and Zhou H., et al. (2018). Increased H3K9 methylation and impaired expression of Protocadherins are associated with the cognitive dysfunctions of the Kleefstra syndrome. Nucleic Acids Res. 46, 4950-4965.
    Pubmed KoreaMed CrossRef
  59. Irizarry R.A., Ladd-Acosta C., Wen B., Wu Z., Montano C., Onyango P., Cui H., Gabo K., Rongione M., and Webster M. (2009). The human colon cancer methylome shows similar hypo-and hypermethylation at conserved tissue-specific CpG island shores. Nat. Genet. 41, 178-186.
    Pubmed KoreaMed CrossRef
  60. Ito S., D'Alessio A.C., Taranova O.V., Hong K., Sowers L.C., and Zhang Y. (2010). Role of Tet proteins in 5mC to 5hmC conversion, ES-cell self-renewal and inner cell mass specification. Nature 466, 1129-1133.
    Pubmed KoreaMed CrossRef
  61. Jang K.H., Heras C.R., and Lee G. (2022). m6A in the signal transduction network. Mol. Cells 45, 435-443.
    Pubmed KoreaMed CrossRef
  62. Jenuwein T. and Allis C.D. (2001). Translating the histone code. Science 293, 1074-1080.
    Pubmed CrossRef
  63. Johnson A., Li G., Sikorski T.W., Buratowski S., Woodcock C.L., and Moazed D. (2009). Reconstitution of heterochromatin-dependent transcriptional gene silencing. Mol. Cell 35, 769-781.
    Pubmed KoreaMed CrossRef
  64. Jones B., Su H., Bhat A., Lei H., Bajko J., Hevi S., Baltus G.A., Kadam S., Zhai H., and Valdez R. (2008). The histone H3K79 methyltransferase Dot1L is essential for mammalian development and heterochromatin structure. PLoS Genet. 4, e1000190.
    Pubmed KoreaMed CrossRef
  65. Karg E., Smets M., Ryan J., Forné I., Qin W., Mulholland C.B., Kalideris G., Imhof A., Bultmann S., and Leonhardt H. (2017). Ubiquitome analysis reveals PCNA-associated factor 15 (PAF15) as a specific ubiquitination target of UHRF1 in embryonic stem cells. J. Mol. Biol. 429, 3814-3824.
    Pubmed CrossRef
  66. Kaya-Okur H.S., Wu S.J., Codomo C.A., Pledger E.S., Bryson T.D., Henikoff J.G., Ahmad K., and Henikoff S. (2019). CUT&Tag for efficient epigenomic profiling of small samples and single cells. Nat. Commun. 10, 1930.
    Pubmed KoreaMed CrossRef
  67. Kim M.J., Lee H.J., Choi M.Y., Kang S.S., Kim Y.S., Shin J.K., and Choi W.S. (2021). UHRF1 induces methylation of the TXNIP promoter and down-regulates gene expression in cervical cancer. Mol. Cells 44, 146-159.
    Pubmed KoreaMed CrossRef
  68. Kim T. and Buratowski S. (2009). Dimethylation of H3K4 by Set1 recruits the Set3 histone deacetylase complex to 5′ transcribed regions. Cell 137, 259-272.
    Pubmed KoreaMed CrossRef
  69. Kleer C.G., Cao Q., Varambally S., Shen R., Ota I., Tomlins S.A., Ghosh D., Sewalt R.G., Otte A.P., and Hayes D.F. (2003). EZH2 is a marker of aggressive breast cancer and promotes neoplastic transformation of breast epithelial cells. Proc. Natl. Acad. Sci. U. S. A. 100, 11606-11611.
    Pubmed KoreaMed CrossRef
  70. Klein C.J., Botuyan M.V., Wu Y., Ward C.J., Nicholson G.A., Hammans S., Hojo K., Yamanishi H., Karpf A.R., and Wallace D.C. (2011). Mutations in DNMT1 cause hereditary sensory neuropathy with dementia and hearing loss. Nat. Genet. 43, 595-600.
    Pubmed KoreaMed CrossRef
  71. Ko M., Huang Y., Jankowska A.M., Pape U.J., Tahiliani M., Bandukwala H.S., An J., Lamperti E.D., Koh K.P., and Ganetzky R. (2010). Impaired hydroxylation of 5-methylcytosine in myeloid cancers with mutant TET2. Nature 468, 839-843.
    Pubmed KoreaMed CrossRef
  72. Kong S.L., Li H., Tai J.A., Courtois E.T., Poh H.M., Lau D.P., Haw Y.X., Iyer N.G., Tan D.S.W., and Prabhakar S. (2019). Concurrent single-cell RNA and targeted DNA sequencing on an automated platform for comeasurement of genomic and transcriptomic signatures. Clin. Chem. 65, 272-281.
    Pubmed CrossRef
  73. Kouzarides T. (2007). Chromatin modifications and their function. Cell 128, 693-705.
    Pubmed CrossRef
  74. Ku W.L., Nakamura K., Gao W., Cui K., Hu G., Tang Q., Ni B., and Zhao K. (2019). Single-cell chromatin immunocleavage sequencing (scChIC-seq) to profile histone modification. Nat. Methods 16, 323-325.
    Pubmed KoreaMed CrossRef
  75. Kuzmichev A., Nishioka K., Erdjument-Bromage H., Tempst P., and Reinberg D. (2002). Histone methyltransferase activity associated with a human multiprotein complex containing the Enhancer of Zeste protein. Genes Dev. 16, 2893-2905.
    Pubmed KoreaMed CrossRef
  76. Lan F. and Shi Y. (2009). Epigenetic regulation: methylation of histone and non-histone proteins. Sci. China C Life Sci. 52, 311-322.
    Pubmed CrossRef
  77. Langemeijer S., Kuiper R.P., Berends M., Knops R., Aslanyan M.G., Massop M., Stevens-Linders E., van Hoogen P., van Kessel A.G., and Raymakers R.A. (2009). Acquired mutations in TET2 are common in myelodysplastic syndromes. Nat. Genet. 41, 838-842.
    Pubmed CrossRef
  78. Lee D.S., Luo C., Zhou J., Chandran S., Rivkin A., Bartlett A., Nery J.R., Fitzpatrick C., O'Connor C., and Dixon J.R. (2019). Simultaneous profiling of 3D genome structure and DNA methylation in single human cells. Nat. Methods 16, 999-1006.
    Pubmed KoreaMed CrossRef
  79. Lee D.S., Shin J.Y., Tonge P.D., Puri M.C., Lee S., Park H., Lee W.C., Hussein S.M., Bleazard T., and Yun J.Y. (2014). An epigenomic roadmap to induced pluripotency reveals DNA methylation as a reprogramming modulator. Nat. Commun. 5, 5619.
    Pubmed KoreaMed CrossRef
  80. Lee J., Song J.H., Park J.H., Chung M.Y., Lee S.H., Jeon S.B., Park S.H., Hwang J.T., and Choi H.K. (2023). Dnmt1/Tet2-mediated changes in Cmip methylation regulate the development of nonalcoholic fatty liver disease by controlling the Gbp2-Pparγ-CD36 axis. Exp. Mol. Med. 55, 143-157.
    Pubmed KoreaMed CrossRef
  81. Leonhardt H., Page A.W., Weier H.U., and Bestor T.H. (1992). A targeting sequence directs DNA methyltransferase to sites of DNA replication in mammalian nuclei. Cell 71, 865-873.
    Pubmed CrossRef
  82. Li A., Chen Y.S., Ping X.L., Yang X., Xiao W., Yang Y., Sun H.Y., Zhu Q., Baidya P., and Wang X. (2017). Cytoplasmic m6A reader YTHDF3 promotes mRNA translation. Cell Res. 27, 444-447.
    Pubmed KoreaMed CrossRef
  83. Li Y. and Seto E. (2016). HDACs and HDAC inhibitors in cancer development and therapy. Cold Spring Harb. Perspect. Med. 6, a026831.
    Pubmed KoreaMed CrossRef
  84. Lieberman-Aiden E., Van Berkum N.L., Williams L., Imakaev M., Ragoczy T., Telling A., Amit I., Lajoie B.R., Sabo P.J., and Dorschner M.O. (2009). Comprehensive mapping of long-range interactions reveals folding principles of the human genome. Science 326, 289-293.
    Pubmed KoreaMed CrossRef
  85. Liu J., Yue Y., Han D., Wang X., Fu Y., Zhang L., Jia G., Yu M., Lu Z., and Deng X. (2014). A METTL3-METTL14 complex mediates mammalian nuclear RNA N6-adenosine methylation. Nat. Chem. Biol. 10, 93-95.
    Pubmed KoreaMed CrossRef
  86. Liu L., Liu C., Quintero A., Wu L., Yuan Y., Wang M., Cheng M., Leng L., Xu L., and Dong G. (2019). Deconvolution of single-cell multi-omics layers reveals regulatory heterogeneity. Nat. Commun. 10, 470.
    Pubmed KoreaMed CrossRef
  87. Liu N. and Pan T. (2015). RNA epigenetics. Transl. Res. 165, 28-35.
    Pubmed KoreaMed CrossRef
  88. Lund E., Oldenburg A.R., and Collas P. (2014). Enriched domain detector: a program for detection of wide genomic enrichment domains robust against local variations. Nucleic Acids Res. 42, e92.
    Pubmed KoreaMed CrossRef
  89. Luo C., Liu H., Xie F., Armand E.J., Siletti K., Bakken T.E., Fang R., Doyle W.I., Stuart T., and Hodge R.D. (2022). Single nucleus multi-omics identifies human cortical cell regulatory genome diversity. Cell Genom. 2, 100107.
    Pubmed KoreaMed CrossRef
  90. Ma J.Z., Yang F., Zhou C.C., Liu F., Yuan J.H., Wang F., Wang T.T., Xu Q.G., Zhou W.P., and Sun S.H. (2017). METTL14 suppresses the metastatic potential of hepatocellular carcinoma by modulating N6‐methyladenosine‐dependent primary MicroRNA processing. Hepatology 65, 529-543.
    Pubmed CrossRef
  91. Macaulay I.C., Haerty W., Kumar P., Li Y.I., Hu T.X., Teng M.J., Goolam M., Saurat N., Coupland P., and Shirley L.M. (2015). G&T-seq: parallel sequencing of single-cell genomes and transcriptomes. Nat. Methods 12, 519-522.
    Pubmed CrossRef
  92. Maiti A. and Drohat A.C. (2011). Thymine DNA glycosylase can rapidly excise 5-formylcytosine and 5-carboxylcytosine: potential implications for active demethylation of CpG sites. J. Biol. Chem. 286, 35334-35338.
    Pubmed KoreaMed CrossRef
  93. Mateo L.J., Murphy S.E., Hafner A., Cinquini I.S., Walker C.A., and Boettiger A.N. (2019). Visualizing DNA folding and RNA in embryos at single-cell resolution. Nature 568, 49-54.
    Pubmed KoreaMed CrossRef
  94. Meissner A., Gnirke A., Bell G.W., Ramsahoye B., Lander E.S., and Jaenisch R. (2005). Reduced representation bisulfite sequencing for comparative high-resolution DNA methylation analysis. Nucleic Acids Res. 33, 5868-5877.
    Pubmed KoreaMed CrossRef
  95. Meyer K.D. (2019). DART-seq: an antibody-free method for global m6A detection. Nat. Methods 16, 1275-1280.
    Pubmed KoreaMed CrossRef
  96. Mikkelsen T.S., Ku M., Jaffe D.B., Issac B., Lieberman E., Giannoukos G., Alvarez P., Brockman W., Kim T.K., and Koche R.P. (2007). Genome-wide maps of chromatin state in pluripotent and lineage-committed cells. Nature 448, 553-560.
    Pubmed KoreaMed CrossRef
  97. Miller T., Krogan N.J., Dover J., Erdjument-Bromage H., Tempst P., Johnston M., Greenblatt J.F., and Shilatifard A. (2001). COMPASS: a complex of proteins associated with a trithorax-related SET domain protein. Proc. Natl. Acad. Sci. U. S. A. 98, 12902-12907.
    Pubmed KoreaMed CrossRef
  98. Mimitou E.P., Cheng A., Montalbano A., Hao S., Stoeckius M., Legut M., Roush T., Herrera A., Papalexi E., and Ouyang Z. (2019). Multiplexed detection of proteins, transcriptomes, clonotypes and CRISPR perturbations in single cells. Nat. Methods 16, 409-412.
    Pubmed KoreaMed CrossRef
  99. Miura F., Enomoto Y., Dairiki R., and Ito T. (2012). Amplification-free whole-genome bisulfite sequencing by post-bisulfite adaptor tagging. Nucleic Acids Res. 40, e136.
    Pubmed KoreaMed CrossRef
  100. Mohn F., Weber M., Rebhan M., Roloff T.C., Richter J., Stadler M.B., Bibel M., and Schübeler D. (2008). Lineage-specific polycomb targets and de novo DNA methylation define restriction and potential of neuronal progenitors. Mol. Cell 30, 755-766.
    Pubmed CrossRef
  101. Mumbach M.R., Rubin A.J., Flynn R.A., Dai C., Khavari P.A., Greenleaf W.J., and Chang H.Y. (2016). HiChIP: efficient and sensitive analysis of protein-directed genome architecture. Nat. Methods 13, 919-922.
    Pubmed KoreaMed CrossRef
  102. Nagano T., Lubling Y., Várnai C., Dudley C., Leung W., Baran Y., Mendelson Cohen N., Wingett S., Fraser P., and Tanay A. (2017). Cell-cycle dynamics of chromosomal organization at single-cell resolution. Nature 547, 61-67.
    Pubmed KoreaMed CrossRef
  103. Nan X., Ng H.H., Johnson C.A., Laherty C.D., Turner B.M., Eisenman R.N., and Bird A. (1998). Transcriptional repression by the methyl-CpG-binding protein MeCP2 involves a histone deacetylase complex. Nature 393, 386-389.
    Pubmed CrossRef
  104. Ng S., Yue W., Oppermann U., and Klose R. (2009). Dynamic protein methylation in chromatin biology. Cell. Mol. Life Sci. 66, 407-422.
    Pubmed KoreaMed CrossRef
  105. North J.A., Šimon M., Ferdinand M.B., Shoffner M.A., Picking J.W., Howard C.J., Mooney A.M., van Noort J., Poirier M.G., and Ottesen J.J. (2014). Histone H3 phosphorylation near the nucleosome dyad alters chromatin structure. Nucleic Acids Res. 42, 4922-4933.
    Pubmed KoreaMed CrossRef
  106. Okano M., Bell D.W., Haber D.A., and Li E. (1999). DNA methyltransferases Dnmt3a and Dnmt3b are essential for de novo methylation and mammalian development. Cell 99, 247-257.
    Pubmed CrossRef
  107. Okano M., Xie S., and Li E. (1998). Cloning and characterization of a family of novel mammalian DNA (cytosine-5) methyltransferases. Nat. Genet. 19, 219-220.
    Pubmed CrossRef
  108. Oki M., Aihara H., and Ito T. (2007). Role of histone phosphorylation in chromatin dynamics and its implications in diseases. Subcell. Biochem. 41, 319-336.
    Pubmed CrossRef
  109. Otani J., Nankumo T., Arita K., Inamoto S., Ariyoshi M., and Shirakawa M. (2009). Structural basis for recognition of H3K4 methylation status by the DNA methyltransferase 3A ATRX-DNMT3-DNMT3L domain. EMBO Rep. 10, 1235-1241.
    Pubmed KoreaMed CrossRef
  110. Pan X., Hong X., Li S., Meng P., and Xiao F. (2021). METTL3 promotes adriamycin resistance in MCF-7 breast cancer cells by accelerating pri-microRNA-221-3p maturation in a m6A-dependent manner. Exp. Mol. Med. 53, 91-102.
    Pubmed KoreaMed CrossRef
  111. Paris J., Morgan M., Campos J., Spencer G.J., Shmakova A., Ivanova I., Mapperley C., Lawson H., Wotherspoon D.A., and Sepulveda C. (2019). Targeting the RNA m6A reader YTHDF2 selectively compromises cancer stem cells in acute myeloid leukemia. Cell Stem Cell 25, 137-148.e6.
    Pubmed KoreaMed CrossRef
  112. Parthun M. (2007). Hat1: the emerging cellular roles of a type B histone acetyltransferase. Oncogene 26, 5319-5328.
    Pubmed CrossRef
  113. Patil D.P., Chen C.K., Pickering B.F., Chow A., Jackson C., Guttman M., and Jaffrey S.R. (2016). m6A RNA methylation promotes XIST-mediated transcriptional repression. Nature 537, 369-373.
    Pubmed KoreaMed CrossRef
  114. Peng W., Li J., Chen R., Gu Q., Yang P., Qian W., Ji D., Wang Q., Zhang Z., and Tang J. (2019). Upregulated METTL3 promotes metastasis of colorectal Cancer via miR-1246/SPRED2/MAPK signaling pathway. J. Exp. Clin. Cancer Res. 38, 393.
    Pubmed KoreaMed CrossRef
  115. Peterson V.M., Zhang K.X., Kumar N., Wong J., Li L., Wilson D.C., Moore R., McClanahan T.K., Sadekova S., and Klappenbach J.A. (2017). Multiplexed quantification of proteins and transcripts in single cells. Nat. Biotechnol. 35, 936-939.
    Pubmed CrossRef
  116. Ping X.L., Sun B.F., Wang L., Xiao W., Yang X., Wang W.J., Adhikari S., Shi Y., Lv Y., and Chen Y.S. (2014). Mammalian WTAP is a regulatory subunit of the RNA N6-methyladenosine methyltransferase. Cell Res. 24, 177-189.
    Pubmed KoreaMed CrossRef
  117. Piunti A. and Shilatifard A. (2016). Epigenetic balance of gene expression by Polycomb and COMPASS families. Science 352, aad9780.
    Pubmed CrossRef
  118. Pogo B., Allfrey V., and Mirsky A. (1966). RNA synthesis and histone acetylation during the course of gene activation in lymphocytes. Proc. Natl. Acad. Sci. U. S. A. 55, 805-812.
    Pubmed KoreaMed CrossRef
  119. Ponciano-Gómez A., Martínez-Tovar A., Vela-Ojeda J., Olarte-Carrillo I., Centeno-Cruz F., and Garrido E. (2017). Mutations in TET2 and DNMT3A genes are associated with changes in global and gene-specific methylation in acute myeloid leukemia. Tumor Biol. 39, 1010428317732181.
    Pubmed CrossRef
  120. Rea S., Eisenhaber F., O'Carroll D., Strahl B.D., Sun Z.W., Schmid M., Opravil S., Mechtler K., Ponting C.P., and Allis C.D. (2000). Regulation of chromatin structure by site-specific histone H3 methyltransferases. Nature 406, 593-599.
    Pubmed CrossRef
  121. Reyes M., Billman K., Hacohen N., and Blainey P.C. (2019). Simultaneous profiling of gene expression and chromatin accessibility in single cells. Adv. Biosyst. 3, 1900065.
    Pubmed KoreaMed CrossRef
  122. Rodriguez-Meira A., Buck G., Clark S.A., Povinelli B.J., Alcolea V., Louka E., McGowan S., Hamblin A., Sousos N., and Barkas N. (2019). Unravelling intratumoral heterogeneity through high-sensitivity single-cell mutational analysis and parallel RNA sequencing. Mol. Cell 73, 1292-1305.e8.
    Pubmed KoreaMed CrossRef
  123. Rotem A., Ram O., Shoresh N., Sperling R.A., Goren A., Weitz D.A., and Bernstein B.E. (2015). Single-cell ChIP-seq reveals cell subpopulations defined by chromatin state. Nat. Biotechnol. 33, 1165-1172.
    Pubmed KoreaMed CrossRef
  124. Roth S.Y., Denu J.M., and Allis C.D. (2001). Histone acetyltransferases. Annu. Rev. Biochem. 70, 81-120.
    Pubmed CrossRef
  125. Rowley M.J. and Corces V.G. (2018). Organizational principles of 3D genome architecture. Nat. Rev. Genet. 19, 789-800.
    Pubmed KoreaMed CrossRef
  126. Russler-Germain D.A., Spencer D.H., Young M.A., Lamprecht T.L., Miller C.A., Fulton R., Meyer M.R., Erdmann-Gilmore P., Townsend R.R., and Wilson R.K. (2014). The R882H DNMT3A mutation associated with AML dominantly inhibits wild-type DNMT3A by blocking its ability to form active tetramers. Cancer Cell 25, 442-454.
    Pubmed KoreaMed CrossRef
  127. Santos-Rosa H., Schneider R., Bannister A.J., Sherriff J., Bernstein B.E., Emre N., Schreiber S.L., Mellor J., and Kouzarides T. (2002). Active genes are tri-methylated at K4 of histone H3. Nature 419, 407-411.
    Pubmed CrossRef
  128. Satpathy A.T., Saligrama N., Buenrostro J.D., Wei Y., Wu B., Rubin A.J., Granja J.M., Lareau C.A., Li R., and Qi Y. (2018). Transcript-indexed ATAC-seq for precision immune profiling. Nat. Med. 24, 580-590.
    Pubmed KoreaMed CrossRef
  129. Saxonov S., Berg P., and Brutlag D.L. (2006). A genome-wide analysis of CpG dinucleotides in the human genome distinguishes two distinct classes of promoters. Proc. Natl. Acad. Sci. U. S. A. 103, 1412-1417.
    Pubmed KoreaMed CrossRef
  130. Schoenfelder S. and Fraser P. (2019). Long-range enhancer-promoter contacts in gene expression control. Nat. Rev. Genet. 20, 437-455.
    Pubmed CrossRef
  131. Schuhmacher M.K., Kudithipudi S., Kusevic D., Weirich S., and Jeltsch A. (2015). Activity and specificity of the human SUV39H2 protein lysine methyltransferase. Biochim. Biophys. Acta 1849, 55-63.
    Pubmed CrossRef
  132. Shahi P., Kim S.C., Haliburton J.R., Gartner Z.J., and Abate A.R. (2017). Abseq: ultrahigh-throughput single cell protein profiling with droplet microfluidic barcoding. Sci. Rep. 7, 44447.
    Pubmed KoreaMed CrossRef
  133. Skene P.J. and Henikoff S. (2017). An efficient targeted nuclease strategy for high-resolution mapping of DNA binding sites. Elife 6, e21856.
    Pubmed KoreaMed CrossRef
  134. Smallwood S.A., Lee H.J., Angermueller C., Krueger F., Saadeh H., Peat J., Andrews S.R., Stegle O., Reik W., and Kelsey G. (2014). Single-cell genome-wide bisulfite sequencing for assessing epigenetic heterogeneity. Nat. Methods 11, 817-820.
    Pubmed KoreaMed CrossRef
  135. Smith Z.D. and Meissner A. (2013). DNA methylation: roles in mammalian development. Nat. Rev. Genet. 14, 204-220.
    Pubmed CrossRef
  136. Song L. and Crawford G.E. (2010). DNase-seq: a high-resolution technique for mapping active gene regulatory elements across the genome from mammalian cells. Cold Spring Harb. Protoc. 2010, pdb.prot5384.
    Pubmed KoreaMed CrossRef
  137. Spellmon N., Holcomb J., Trescott L., Sirinupong N., and Yang Z. (2015). Structure and function of SET and MYND domain-containing proteins. Int. J. Mol. Sci. 16, 1406-1428.
    Pubmed KoreaMed CrossRef
  138. Spencer D.H., Russler-Germain D.A., Ketkar S., Helton N.M., Lamprecht T.L., Fulton R.S., Fronick C.C., O'Laughlin M., Heath S.E., and Shinawi M. (2017). CpG island hypermethylation mediated by DNMT3A is a consequence of AML progression. Cell 168, 801-816.e13.
    Pubmed KoreaMed CrossRef
  139. Stevens T.J., Lando D., Basu S., Atkinson L.P., Cao Y., Lee S.F., Leeb M., Wohlfahrt K.J., Boucher W., and O'Shaughnessy-Kirwan A. (2017). 3D structures of individual mammalian genomes studied by single-cell Hi-C. Nature 544, 59-64.
    Pubmed KoreaMed CrossRef
  140. Stoeckius M., Hafemeister C., Stephenson W., Houck-Loomis B., Chattopadhyay P.K., Swerdlow H., Satija R., and Smibert P. (2017). Simultaneous epitope and transcriptome measurement in single cells. Nat. Methods 14, 865-868.
    Pubmed KoreaMed CrossRef
  141. Strahl B.D. and Allis C.D. (2000). The language of covalent histone modifications. Nature 403, 41-45.
    Pubmed CrossRef
  142. Suraweera A., O'Byrne K.J., and Richard D.J. (2018). Combination therapy with histone deacetylase inhibitors (HDACi) for the treatment of cancer: achieving the full therapeutic potential of HDACi. Front. Oncol. 8, 92.
    Pubmed KoreaMed CrossRef
  143. Szabo Q., Donjon A., Jerković I., Papadopoulos G.L., Cheutin T., Bonev B., Nora E.P., Bruneau B.G., Bantignies F., and Cavalli G. (2020). Regulation of single-cell genome organization into TADs and chromatin nanodomains. Nat. Genet. 52, 1151-1157.
    Pubmed KoreaMed CrossRef
  144. Tachibana M., Sugimoto K., Nozaki M., Ueda J., Ohta T., Ohki M., Fukuda M., Takeda N., Niida H., and Kato H. (2002). G9a histone methyltransferase plays a dominant role in euchromatic histone H3 lysine 9 methylation and is essential for early embryogenesis. Genes Dev. 16, 1779-1791.
    Pubmed KoreaMed CrossRef
  145. Tahiliani M., Koh K.P., Shen Y., Pastor W.A., Bandukwala H., Brudno Y., Agarwal S., Iyer L.M., Liu D.R., and Aravind L. (2009). Conversion of 5-methylcytosine to 5-hydroxymethylcytosine in mammalian DNA by MLL partner TET1. Science 324, 930-935.
    Pubmed KoreaMed CrossRef
  146. Waddington C.H. (1942). The epigenotype. Endeavour 1, 18-20.
    Pubmed CrossRef
  147. Wang X., Zhao B.S., Roundtree I.A., Lu Z., Han D., Ma H., Weng X., Chen K., Shi H., and He C. (2015). N6-methyladenosine modulates messenger RNA translation efficiency. Cell 161, 1388-1399.
    Pubmed KoreaMed CrossRef
  148. Wang Y., Yuan P., Yan Z., Yang M., Huo Y., Nie Y., Zhu X., Qiao J., and Yan L. (2021). Single-cell multiomics sequencing reveals the functional regulatory landscape of early embryos. Nat. Commun. 12, 1247.
    Pubmed KoreaMed CrossRef
  149. Weber A.R., Krawczyk C., Robertson A.B., Kuśnierczyk A., Vågbø C.B., Schuermann D., Klungland A., and Schär P. (2016). Biochemical reconstitution of TET1-TDG-BER-dependent active DNA demethylation reveals a highly coordinated mechanism. Nat. Commun. 7, 10806.
    Pubmed KoreaMed CrossRef
  150. Weber M., Davies J.J., Wittig D., Oakeley E.J., Haase M., Lam W.L., and Schuebeler D. (2005). Chromosome-wide and promoter-specific analyses identify sites of differential DNA methylation in normal and transformed human cells. Nat. Genet. 37, 853-862.
    Pubmed CrossRef
  151. Wei C.L., Wu Q., Vega V.B., Chiu K.P., Ng P., Zhang T., Shahab A., Yong H.C., Fu Y., and Weng Z. (2006). A global map of p53 transcription-factor binding sites in the human genome. Cell 124, 207-219.
    Pubmed CrossRef
  152. Wei Y., Mizzen C.A., Cook R.G., Gorovsky M.A., and Allis C.D. (1998). Phosphorylation of histone H3 at serine 10 is correlated with chromosome condensation during mitosis and meiosis in Tetrahymena. Proc. Natl. Acad. Sci. U. S. A. 95, 7480-7484.
    Pubmed KoreaMed CrossRef
  153. Xu Z., Lee D.S., Chandran S., Le V.T., Bump R., Yasis J., Dallarda S., Marcotte S., Clock B., and Haghani N. (2022). Structural variants drive context-dependent oncogene activation in cancer. Nature 612, 564-572.
    Pubmed KoreaMed CrossRef
  154. Yan R., Gu C., You D., Huang Z., Qian J., Yang Q., Cheng X., Zhang L., Wang H., and Wang P. (2021). Decoding dynamic epigenetic landscapes in human oocytes using single-cell multi-omics sequencing. Cell Stem Cell 28, 1641-1656.e7.
    Pubmed CrossRef
  155. Yang X.J. and Seto E. (2008). Lysine acetylation: codified crosstalk with other posttranslational modifications. Mol. Cell 31, 449-461.
    Pubmed KoreaMed CrossRef
  156. Yuan W., Xu M., Huang C., Liu N., Chen S., and Zhu B. (2011). H3K36 methylation antagonizes PRC2-mediated H3K27 methylation. J. Biol. Chem. 286, 7983-7989.
    Pubmed KoreaMed CrossRef
  157. Zaidi S., Choi M., Wakimoto H., Ma L., Jiang J., Overton J.D., Romano-Adesman A., Bjornson R.D., Breitbart R.E., and Brown K.K. (2013). De novo mutations in histone-modifying genes in congenital heart disease. Nature 498, 220-223.
    Pubmed KoreaMed CrossRef
  158. Zhang C., Samanta D., Lu H., Bullen J.W., Zhang H., Chen I., He X., and Semenza G.L. (2016). Hypoxia induces the breast cancer stem cell phenotype by HIF-dependent and ALKBH5-mediated m6A-demethylation of NANOG mRNA. Proc. Natl. Acad. Sci. U. S. A. 113, E2047-E2056.
    Pubmed KoreaMed CrossRef
  159. Zhang Z., Theler D., Kaminska K.H., Hiller M., de la Grange P., Pudimat R., Rafalska I., Heinrich B., Bujnicki J.M., and Allain F.H.T. (2010). The YTH domain is a novel RNA binding domain. J. Biol. Chem. 285, 14701-14710.
    Pubmed KoreaMed CrossRef
  160. Zhao J., Li B., Ren Y., Liang T., Wang J., Zhai S., Zhang X., Zhou P., Zhang X., and Pan Y. (2021). Histone demethylase KDM4A plays an oncogenic role in nasopharyngeal carcinoma by promoting cell migration and invasion. Exp. Mol. Med. 53, 1207-1217.
    Pubmed KoreaMed CrossRef
  161. Zheng G., Dahl J.A., Niu Y., Fedorcsak P., Huang C.M., Li C.J., Vågbø C.B., Shi Y., Wang W.L., and Song S.H. (2013). ALKBH5 is a mammalian RNA demethylase that impacts RNA metabolism and mouse fertility. Mol. Cell 49, 18-29.
    Pubmed KoreaMed CrossRef
  162. Zhu C., Yu M., Huang H., Juric I., Abnousi A., Hu R., Lucero J., Behrens M.M., Hu M., and Ren B. (2019). An ultra high-throughput method for single-cell joint analysis of open chromatin and transcriptome. Nat. Struct. Mol. Biol. 26, 1063-1070.
    Pubmed KoreaMed CrossRef

Article

Minireview

Mol. Cells 2023; 46(2): 86-98

Published online February 28, 2023 https://doi.org/10.14348/molcells.2023.0013

Copyright © The Korean Society for Molecular and Cellular Biology.

Epigenetic Regulations in Mammalian Cells: Roles and Profiling Techniques

Uijin Kim and Dong-Sung Lee*

Department of Life Science, University of Seoul, Seoul 02504, Korea

Correspondence to:eaststar0@gmail.com

Received: January 14, 2023; Revised: February 3, 2023; Accepted: February 4, 2023

This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-sa/3.0/.

Abstract

The genome is almost identical in all the cells of the body. However, the functions and morphologies of each cell are different, and the factors that determine them are the genes and proteins expressed in the cells. Over the past decades, studies on epigenetic information, such as DNA methylation, histone modifications, chromatin accessibility, and chromatin conformation have shown that these properties play a fundamental role in gene regulation. Furthermore, various diseases such as cancer have been found to be associated with epigenetic mechanisms. In this study, we summarized the biological properties of epigenetics and single-cell epigenomic profiling techniques, and discussed future challenges in the field of epigenetics.

Keywords: 3D chromatin structure, DNA methylation, histone modification, RNA modification, single-cell epigenomics

INTRODUCTION

In 1942, Conrad Waddington defined “epigenetics” as a change in phenotype without a change in genotype (Waddington, 1942). Based on the current understanding from several studies, epigenetics is that the total DNA content in somatic cells is the same and there is no change in the existing DNA sequence, whereas the inheritance of gene expression patterns markedly varies among various cell types depending on changes in the chromatin state (Felsenfeld, 2014). Epigenetic mechanisms, in addition to DNA templates, can affect gene regulation during and after transcription and translation (Halušková, 2010). These properties can be profiled by various sequencing techniques. In addition, recent single-cell based profiling methods provide an opportunity to identify cell-to-cell variability. In this review, we provide a general overview of representative epigenetic phenomena, such as DNA methylation and histone modification, and epigenome profiling methods.

HISTONE MODIFICATIONS

In eukaryotic cells, DNA is surrounded by chromatin in the nucleus (Jenuwein and Allis, 2001). Eukaryotic chromatin is a highly condensed that is structure essential for basic nuclear processes such as transcription and replication. Chromatin is divided into weakly and strongly condensed regions. The weakly condensed region is a region called euchromatin where transcription is generally active, shereas the strongly condensed region is a region called heterochromatin where gene expression is restricted (Back, 1976). The nucleosome is the basic unit of chromatin and consists of approximately 147 DNA base pairs and a histone octamer with two subunits H2A, H2B, H3, and H4 (Jenuwein and Allis, 2001). These histone tails of chromatin can be modified post-translationally by acetylation, methylation, and phosphorylation (Strahl and Allis, 2000) (Fig. 1). These post-translational covalent modifications are accumulated by epigenetic mechanisms and can alter the chromatin state and subsequent gene expression (Kouzarides, 2007) (Fig. 2). Histone modifications are mainly profiled using chromatin immunoprecipitation followed by sequencing (ChIP-seq) (Barski et al., 2007; Mikkelsen et al., 2007). In recent studies, histone modification information has been analyzed using Tn5 transposase-mediated tagmentation techniques such as cleavage under target and tagmentation (CUT&TAG) with few cells (Kaya-Okur et al., 2019) (Table 1).

Histone acetylation

Histone acetylation is the process by which the acetyl group of acetyl-CoA is transferred to the NH3+ group of the histone lysine. The addition of an acetyl group neutralizes the positive state of lysine and reduces the binding of histone proteins to DNA, making the DNA open and accessible to transcription factors (Bannister and Kouzarides, 2011). Histone hyperacetylation is a hallmark of transcriptional activity (Clayton et al., 1993; Pogo et al., 1966). The balance of histone acetyltransferases (HATs) and histone deacetylases (HDACs) is an important factor in the regulation of histone acetylation. HATs can be divided into two classes based on their subcellular localization and function (Parthun, 2007). A-type HATs are nuclear enzymes involved in the regulation of gene expression through the acetylation of nucleosomal histones in the chromatin context. B-type HATs are located in the cytoplasm and are responsible for acetylating newly synthesized histones prior to their transport from the cytoplasm to the nucleus where they assemble into nucleosomes (Roth et al., 2001) (Table 2).

HDACs oppose the effects of HATs and reverse lysine acetylation. In humans, there are four distinct classes of 18 HDACs: class I (Rpd3-like) (HDAC1-3 and HDAC8) and class II (Hda1-like) (HDAC4-7, HDAC9, and HDAC10), class III NAD-dependent enzymes of (Sir2-like) (SIRT1-7), and class IV for the single-member HDAC11 (Yang and Seto, 2008). In general, they are involved in multiple signaling pathways, and have relatively low specificity for particular acetyl groups, allowing a single enzyme to deacetylate multiple sites within histones. Various HDAC inhibitors have been developed and used to treat tumors. They can also induce cancer cell cycle arrest, differentiation, and apoptosis (Bose et al., 2014; Suraweera et al., 2018) (Table 2).

Histone phosphorylation

Phosphorylation is one of the most common post-translational modifications that occur on serine, threonine, and tyrosine residues of histone proteins (North et al., 2014). Similar to histone acetylation, this modification is highly dynamic and its levels are regulated by the addition and removal phosphate groups (Oki et al., 2007). Phosphoryl groups are transferred from ATP to the hydroxyl groups of amino acids by kinases, thereby adding a negative charge to histone proteins. In mammalian cells, H3S10 phosphorylation, which is mediated by Aurora -B kinase, is essential for mitosis and meiosis (Wei et al., 1998). This is because H3S10 phosphorylation dissociates the HP1 protein, which contributes to heterochromatin formation recruited by H3K9me3 in the interphase, from chromatin and prevents the formation of condensed heterochromatin. In addition, phosphorylation of the 139th serine group of H2AX is a histone modification induced by ATM and ATR. These modifications are involved in various DNA damage response pathways, including non-homologous end joining and homologous recombination (Cheung et al., 2005; Downs et al., 2004).

Histone methylation

Histone methylation usually occurs on the side chains of lysine and arginine and is one of the most important post-transcriptional modifications. Unlike acetylation and phosphorylation, histone methylation does not affect the charge on histone proteins. Histone lysine residues can be mono-, di-, or tri-methylated, while arginine residues can be mono- or di-methylated (Lan and Shi, 2009; Ng et al., 2009). Most histone lysine methyltransferases (HKMTs) have an evolutionarily well-conserved sequence motif identified in Drosophila called Su(var)3-9, Enhancer-of-zeste, and Trithorax (SET) (Schuhmacher et al., 2015; Spellmon et al., 2015).

H3K9 methylation is associated with heterochromatin. The methylation of H3K9 is driven by SUV39H1/2, G9a, G9a-like protein (GLP), and SETDB1 (Fritsch et al., 2010). SETDB1 co-translationally catalyzes mono- and dimethylation when H3K9 binds to ribosomes. G9a and GLP can form homomeric and heteromeric complexes and are involved in the formation of H3K9me1 and H3K9me2 (Tachibana et al., 2002). SUV39H1/2 is a key enzyme for H3K9me3 in the pericentromeric heterochromatin (Rea et al., 2000). H3K4 methylation is enriched in enhancer regions, promoter regions, and transcription start sites and is usually associated with the transcriptional activation of nearby genes. H3K4me1 and H3K4me3 are distributed in the enhancer and promoter regions, respectively, and H3K4me2 is distributed in the replication origin region and the 5’ end of genes (Heintzman et al., 2007; Kim and Buratowski, 2009; Santos-Rosa et al., 2002). Their distribution locations are related to their functions. Set1, a H3K4 methyltransferase identified in yeast, operates in COMPASS, a complex protein related to Set1 (Briggs et al., 2001; Miller et al., 2001). This enzyme is well conserved from yeast to humans and is responsible for H3K4 methylation. H3K27 methylation is induced by PRC2, a complex of polycomb group proteins. PRC2 has four core subunits (Ezh2, Suz12, EED, and RbAP46/48), and EZh2 catalyzes methylation (Cao et al., 2002; Kuzmichev et al., 2002). H3K27me2 and H3K27me3 are the hallmarks of gene repression (Banaszynski et al., 2013; Barski et al., 2007) (Fig. 2). Conversely, H3K27me1 is associated with transcriptional promotion and is distributed in the promoter regions of the active genes (Barski et al., 2007). H3K36 and H3K79 methylation are considered to be active markers distributed in actively transcribed chromatin regions. H3K36 can be mono- and demethylated by NSD1-3 and ASH1L, and trimethylation is catalyzed by SETD2 (Eram et al., 2014). H3K36 methylation can inhibit the activity of PRC2, preventing H3K27 methylation catalyzed by PRC2 (Yuan et al., 2011). In mammals, H3K79 is methylated by DOT1L. Unlike other HKMTs, DOT1L does not contain a SET domain because it is located in a globular histone core that is difficult for H3K79 to access (Jones et al., 2008) (Table 2).

Histone methylation in cancer

Aberrant histone modifications can affect chromosomal segregation or abnormal regulation of oncogenes and/or tumor suppressor genes (Table 2). Histone modification, which is frequently observed in cancer cells, is the loss of HDAC-mediated acetylation (Li and Seto, 2016). SIRT1 and deacetylase activities are upregulated in various tumor types. In addition to the loss of acetylation, gene silencing due to increased H3K27me3 due to EZH2 overexpression has been implicated in the progression of several solid malignancies, such as breast cancer (Kleer et al., 2003). Overexpression of lncRNA HOTAIR in ovarian cancer recruits EZH2 and alters the H3K27me3 landscape (Dai et al., 2021). It has also been reported that histone demethylase lysine-specific demethylase 4 A promotes the progression of nasopharyngeal carcinoma by promoting hypoxia-inducible factor-1α expression (Zhao et al., 2021). Aberrant histone modifications are closely related to cancer, and histone-modifying enzyme inhibitors such as HDAC inhibitors are being actively studied and developed.

DNA METHYLATION

DNA methylation was first reported in 1948, and its role in gene regulation was first suggested in the mid-1970s (Holliday and Pugh, 1975; Hotchkiss, 1948). In mammalian DNA, there are many 5-methylcytosine (5mC) in sequences where cytosine and guanine are connected in the 5' to 3' direction (Coulondre et al., 1978). Most DNA methylations are stable and play important roles during development and the cell cycle in several epigenetic processes, such as genomic imprinting and X-chromosome inactivation (Smith and Meissner, 2013). DNA methylation plays an important role in controlling the epigenetic environment during reprogramming of somatic cells into pluripotent stem cells (Lee et al., 2014), which is mediated by DNA methyltransferase enzymes (DNMTs) (Table 2). 5mC is mainly profiled using whole-genome bisulfite sequencing (BS-seq) (Cokus et al., 2008). In addition, techniques such as reduced representation bisulfite sequencing (RRBS) and methylated DNA immunoprecipitation sequencing (MeDIP-seq) have been developed to profile the DNA methylation information (Meissner et al., 2005; Weber et al., 2005) (Table 1).

Location of DNA methylation

In the mammalian genome, CpG islands are DNA sequences approximately 1000 base pairs in length with a higher CpG density than the rest of the genome (Bird et al., 1985). Most gene promoters (more than 2/3), particularly promoters of housekeeping genes, are embedded in CpG islands (Saxonov et al., 2006). In general, CpG sites in promoter regions within CpG islands are not methylated differently from the other CpG sites (Bird et al., 1985). Silencing of gene expression by methylation of promoter DNA is stable and long-lasting, unlike transcriptional repression by histone modifications (Mohn et al., 2008). Because of these properties, methylation of CpG islands is an important epigenetic mechanism that regulates imprinted genes and gene expression during development and differentiation. Unlike promoter methylation, gene body DNA methylation is positively correlated with gene expression and is considered a characteristic of transcribed genes in cells (Ball et al., 2009). CpG islands within genes or gene bodies can reveal specific methylation differences between tissues or cancer samples. However, CpG islands in promoter regions show little difference in methylation and specific differences at some distance from the CpG islands (called CpG island shores) (Irizarry et al., 2009).

Writing and erasing DNA methylation

DNA methylation consists of three stages: de novo DNA methylation, maintenance, and demethylation (Fig. 3). DNMT3A and DNMT3B, known as de novo methyltransferases, consist of three main domains: the Pro-Trp-Trp-Pro (PWWP), ATRX-DNMT3-DNMT3L (ADD), and MTase domains (Okano et al., 1998; 1999). The ADD domain binds to the unmodified K4 residue of the H3 tail, until it binds to the MTase domain and acts as an inhibitor (Guo et al., 2015). When the ADD domain binds to unmodified H3K4, the ADD domain unbinds from the MTase domain and enables DNA methylation (Otani et al., 2009). As the ADD domain is repelled by the increasing number of methyl residues in H3K4, DNA methylation does not normally occur in CpG-rich promoters of H3K4me3 enriched genes (Piunti and Shilatifard, 2016). As transcription proceeds, the PWWP domain binds to H3K36me3 generated by the histone methyltransferase SETD2 to induce DNA methylation in the gene body (Dhayalan et al., 2010). Among de novo methylations, only symmetrical CpG methylation is maintained during DNA replication. This depends on the activity of DNMT1 and UHRF1, an E3 ubiquitin-protein ligase with five conserved domains (Arita et al., 2012). It works together with the TTD and PHD domains of UHRF1 to recognize and bind to H3K9me3, thereby loading DNMT1 onto the newly synthesized DNA substrate (Karg et al., 2017). Therefore, DNMT1 is located on the replication pork where newly synthesized hemimethylated DNA is formed during DNA replication (Leonhardt et al., 1992). DNMT1 is called maintenance DNMT because it maintains the pattern of DNA methylation. DNA methylation can be erased by passive or active demethylation. Passive demethylation leads to replication-dependent dilution of 5mC due to defects in the maintenance methylation mechanism that copies methylation patterns during DNA replication (Howell et al., 2001). Passive demethylation is biologically important for erasing DNA methylation in preimplantation embryos and primordial germ cells. Active DNA demethylation mechanisms have been found to be mediated by Tet1, Tet2, and Tet3 enzymes. The TET protein oxidizes 5mC to produce 5-hydroxymethylcytosine (5hmC) and undergoes demethylation (Ito et al., 2010; Tahiliani et al., 2009). 5hmC can be further oxidized to generate 5fC and 5caC, which can be removed and converted to an unmethylated cytosine by the DNA glycosylase (TDG and SMUG1) and base excision repair pathways, respectively (Maiti and Drohat, 2011; Weber et al., 2016) (Table 2).

DNA methylation crosstalk

DNA methylation and histone modification work together to regulate transcription. Because DNMTs generally suppress gene regions through methylation, they inhibit gene expression by interacting with enzymes that regulate histone modification. DNMT1 and DNMT3a restrict gene expression by binding to SUV39H1, an enzyme that methylates H3K9 (Fuks et al., 2000). In addition, DNMT1 and DNMT3b bind to HDACs and regulate gene expression (Fuks et al., 2000; Geiman et al., 2004). Methyl-binding proteins, such as MeCP2 and UHRF, enhance gene repression by interacting with methylated DNA and histones (Nan et al., 1998). Although the interaction between RNA and DNA modifications is not clearly defined, recent studies have reported that high N6-methyl adenosine (m6A) modifications in esophageal squamous cell carcinoma cells lead to DNA demethylation, altering chromatin accessibility and affecting gene transcription (Deng et al., 2022).

DNA methylation in multiple diseases

DNA methylation is involved in various diseases such as brain disorders and cancer (Table 2). For example, an autosomal-dominant mutation in the N-terminal regulatory domain of DNMT1 was identified in patients with hereditary sensory and autonomic neuropathy type 1, who presented with dementia, hearing loss, and narcolepsy in adulthood (Klein et al., 2011). DNMT3A is associated with the development of acute myeloid leukemia (AML), and TET2 mutations are considered a common epigenetic marker in several hematological malignancies including AML, chronic myelomonocytic leukemia, and lymphomas {Langemeijer, 2009, Acquired mutations in TET2 are common in myelodysplastic syndromes}(Langemeijer et al., 2009; Spencer et al., 2017). Overexpression of UHRF1 promotes hypermethylation of the promoter of thioredoxin-interacting protein (TXNIP), a tumor suppressor gene, and downregulates TXNIP expression in cervical cancer, contributing to carcinogenesis (Kim et al., 2021). The DNMT3A mutation is a missense mutation of Arginine 882 (R882) in the MTase domain, which interferes with DNMT3A formation and reduces the methylation activity of the enzyme (Russler-Germain et al., 2014). Conversely, TET2 mutations induce hypermethylation of enhancer regions in myeloid malignancies (Ko et al., 2010). It is still unclear how two mutants with opposite functions can achieve similar phenotypes. A recent study on patients with AML demonstrated that mutations in DNMT3A and TET2 can cause irregular DNA methylation patterns and transcriptional expression levels in genes known to be involved in AML pathogenesis (Ponciano-Gómez et al., 2017). In addition, Lee et al. (2023) reported that the regulation of C-Maf-inducing protein methylation mediated by DNMT1 and TET2 was correlated with nonalcoholic fatty liver disease.

CHROMATIN CONFORMATION

In mammalian cells, DNA forms nucleosomes, which are arranged into higher-order chromatin structures that play important roles in regulating the cell cycle, replication, development and gene function. The three-dimensional chromatin structure includes cis-regulatory interactions such as enhancer-promoter interactions and repressive interactions such as lamina-associated domains (LADs) and is mediated by structural elements such as CCCTC-binding factor (CTCF) and cohesin (Huang et al., 2021; Rowley and Corces, 2018; Schoenfelder and Fraser, 2019).

Enhancers, a representative cis-regulatory element, are usually several kilobases different from gene promoters but can be involved in transcriptional regulation through reduced spatial proximity to promoters by forming chromatin looping and folding. Chromatin conformation capture (3C) profiles the interactions between these specific genomic regions (Dekker et al., 2002). A recent technique, Hi-C, allows global quantification of all interactions present in the nucleus. Based on the Hi-C data, it was possible to analyze compartments, which are sets of chromosomal regions with similar, long-range Hi-C contact patterns and self-interacting genomic regions called topologically associated domains (TADs) (Dixon et al., 2012; Lieberman-Aiden et al., 2009). Compartment A is associated with open chromatin, and Compartment B is associated with closed chromatin and is specific to the cell type (Dixon et al., 2012). Previous studies have reported that TADs are well conserved among various cell types and species. However, multiple methods based on Hi-C have been developed at the single-cell level, and recent studies have shown that chromatin contacts, such as TAD structures, vary considerably at the single-cell level (Stevens et al., 2017). In general, the frequency of interactions within TADs is high and the interaction between TADs is generally low. CTCF is an important factor in regulating TAD structure and is involved in the insulation between TADs (Szabo et al., 2020). The disruption of TAD boundaries can affect gene expression and is associated with various diseases and cancers. A recent study reported that the combination of genome profiling and CRISPR-Cas9 genome engineering could identify regions with repetitive changes in the 3D genome structure and predict oncogene activity (Xu et al., 2022). Nuclear lamina and constituent filament proteins, A/B type lamins, are located in the nuclear envelope. LADs are heterochromatic regions that constitute approximately 40% of the genome and are in contact with the nuclear lamina. The LAD region is enriched in H3K9me2/3 and H3K27me3, and a few genes within the LAD are expressed (Guelen et al., 2008; Lund et al., 2014).

RNA MODIFICATION

Mammalian RNA undergoes numerous post-transcriptional chemical modifications. Although these RNA modifications were discovered in the 1970s, their importance has not yet been highlighted. Over the past decade, several studies have shown that RNA modifications play an important role in regulating gene expression, similar to the epigenetic modifications of DNA and histones (Helm and Motorin, 2017).

m6A is the most abundant endogenous RNA modification in eukaryotes. m6A is precisely controlled by three protein groups: “writers” that install m6A residues along target RNA transcripts, “erasers” that remove modifications at specific sites, and “readers” that recognize modified regions. m6A RNA methylation is catalyzed by “writer” proteins, m6A methyltransferase-like 3 and 14 (METTL3 and METTL14). METTL3 and METTL14 form stable heterodimer complexes (Bokar et al., 1997; Liu et al., 2014). In addition, the METTL3-METTL14 complex interacts with Wilms tumor 1-associated protein to target a wide range of RNA substrates and install m6A (Ping et al., 2014). m6A demethylation is catalyzed by the AlkB family of non-heme Fe(II)/α-KG-dependent dioxygenases. Representative major human AlkB family members include fat mass- and obesity-associated protein (FTO) and alkylation repair homolog protein 5 (ALKBH5). FTO is an RNA demethylase first discovered in mammalian cells that removes m6A by generating N6-hydroxymethyladenosine and N6-formyladenosine, which can be hydrolyzed into adenine through continuous oxidation over several hours (Fu et al., 2013). ALKBH5 catalyzes the m6A-to-A conversion by directly removing the methyl group (Jang et al., 2022; Zheng et al., 2013). The YT521-B homology (YTH) domain-containing protein family recognizes and binds to m6A. YTHDC1 is located in the nucleus and is characterized by various RNA splicing regulators, such as serine-arginine repeat proteins. It recognizes m6A on the lncRNA XIST and mediates X chromosome silencing (Patil et al., 2016; Zhang et al., 2010). YTHDF1 and YTHDF3 regulate translation efficiency by interacting with the ribosome of the target RNA, and YTHDF2 promotes the degradation of m6A-modified RNA by recruiting deadenylation enzyme complexes, thereby affecting RNA stability (Du et al., 2016; Li et al., 2017; Wang et al., 2015).

m6A modification is associated with various diseases and cancers. METTL3 promotes the maturation of mir-1246 by methylating pri-mir-1246 and down-regulating the anti-oncogene SPRED2, thereby improving the tumor metastasis ability of colorectal cancer (Peng et al., 2019). In addition, METTL3 is also associated with prostatitis and Aicardi syndrome, FTO is an oncogene in AML, breast cancer and colorectal cancer, and YTHDF1 and YTHDF2 are associated with pancreatic cancer and breast cancer, respectively (Huang et al., 2019; Liu and Pan, 2015; Pan et al., 2021).

SINGLE-CELL EPIGENOMIC PROFILING TECHNIQUES

Several techniques have been developed to profile epigenetic regulation (Table 1). However, although these bulk-cell profiling methods showed an average signal for a cell population, it was difficult to represent cell-to-cell variation within tissue, such as gene expression heterogeneity. Single-cell epigenomic analysis has the potential to overcome these limitations and to elucidate gene regulatory mechanisms across diverse cellular environments.

Single-cell ChIP-seq (scChIP-seq) was the first reported technique for profiling histone modifications at the single-cell level. scChIp-seq separates single cells into droplets containing lysis buffer and micrococcal nuclease (MNase), followed by barcoding before immunoprecipitation (Rotem et al., 2015). Since then, several technologies have been developed, such as single-cell chromatin immunocleavage followed by sequencing, chromatin integration labeling sequencing, single-cell cleavage under targets and release using nucleases (scCUT&RUN), and CUT&TAG (Bartosovic et al., 2021; Harada et al., 2019; Kaya-Okur et al., 2019; Ku et al., 2019). Several single-cell studies have confirmed that cell-to-cell variations in histone modifications are correlated with heterogeneity in gene expression. For example, measurements of H3K4me2 levels within mouse embryonic stem cell populations revealed significant variation, which was observed in gene enhancers and transcriptionally repressed genes (Rotem et al., 2015). In addition, integrating single-cell-level H3K4me3 profiling and scRNA-seq in the mouse brain confirmed cellular heterogeneity in oligodendrocyte populations, which appeared homogenous and revealed that they could be dispersed into subpopulations enriched with module-specific genes (Bartosovic et al., 2021).

Single-cell level profiling of DNA methylation has mainly been achieved through bisulfite conversion methods such as single-cell BS-seq (scBS-seq), single-cell RRBS, and post-bisulfite adapter-tagging (Guo et al., 2013; Miura et al., 2012; Smallwood et al., 2014). Bisulfite sequencing is based on the conversion of unmethylated cytosine into uracil. scRRBS generates DNA fragments containing CpG-rich ends by using one or more restriction enzymes, followed by bisulfite sequencing (Guo et al., 2013). scBS-seq was used to perform bisulfite treatment and random priming and extension after cell isolation and lysis (Smallwood et al., 2014). These methods show heterogeneity in DNA methylation in both mouse and human cells. Multi-omics techniques have also been developed to investigate the interaction between DNA methylation heterogeneity, gene expression heterogeneity and other epigenetic data (Table 3). For example, single-cell methylome and transcriptome sequencing (scM&T-seq) have demonstrated a functional link between transcriptional and DNA methylation heterogeneity of gene promoters within specific cell and tissue types in mouse muscle stem cells (Angermueller et al., 2016).

Chromatin accessibility plays an important role in the regulation of gene expression by influencing transcription initiation. Chromatin accessibility can be profiled by assays for transposase-accessible chromatin sequencing (ATAC-seq) and DNase I hypersensitive site sequencing (DNase-seq). These methods measure chromatin accessibility based on enzymatic sensitivity (Buenrostro et al., 2013; Song and Crawford, 2010). Single-cell ATAC-seq (scATAC-seq) and single-cell DNase-seq, similar to other single-cell epigenetic profiling techniques, can identify heterogeneity between cells using the chromatin approach. Cusanovich et al. (2015) appliedcombinatorial indexing to intact nuclei and were able to distinguish between various cell types by profiling thousands of cells. In addition, a recent study performed scATAC-seq and scRNA-seq on DNA and mRNA of the same cell, respectively, and found a positive correlation between gene expression and chromatin accessibility heterogeneity in each cell (Reyes et al., 2019).

Research on 3D genome structure has been greatly improved by bulk cell Hi-C, but cell-to-cell variability of 3D genome features such as TADs or enhancer-promoter contacts could not be accurately reflected. Single-cell Hi-C can be used to perform interaction profiling depending on the proximity ligation region. These techniques based on Hi-C have revealed that chromatin contact varies depending on cell type and developmental status. Using single-cell Hi-C, Nagano et al. (2017) found that mouse embryonic stem cells showed chromosomal condensation in the early G1 phase and extensive reorganization during replication, suggesting that the cell cycle is related to heterogeneity in chromatin contact. In addition, single-nucleus Hi-C removed the previously used biotin-filling step and performed sticky end ligation, revealing that the chromatin structure was uniquely reconstructed during the oocyte-to-zygote transition in mice (Flyamer et al., 2017) (Fig. 4).

Recently, multi-modal omics techniques that can simultaneously profile two or more epigenetic features in a single cell have facilitated the analysis of the correlations between different traits. For example, sn-m3C-seq can simultaneously profile DNA methylation and chromatin conformation at a single-cell level (Lee et al., 2019). In addition, Paired-seq and SNARE-seq can simultaneously profile gene expression and chromatin accessibility information, as well as scM&T-seq and snmC2T-seq can co-profile transcriptome and methylome information (Angermueller et al., 2016; Chen et al., 2019; Luo et al., 2022; Zhu et al., 2019). Many multi-modal omics techniques are still being developed, which will further advance our biological understanding (Table 3).

CONCLUSION

In this review, several characteristics such as DNA methylation and histone modification, which are representative of epigenetic characteristics, were summarized. Mostly, epigenetics focus on molecular biology approaches. However, even if it is not genetic, DNA or histone modifications and three-dimensional chromatin structure have a great influence on the changes that can occur within individual cells. Since the 1980s, scientific interest in the molecular mechanisms of epigenetic control to understand disease development and treatment has continued to grow. Despite numerous studies, several epigenetic mechanisms and patterns remain unknown. However, by integrating advanced techniques sophisticated algorithms, it is now possible to generate and analyze large volumes of epigenetic data. Single-cell multi-omics-based sequencing techniques that are being actively studied can generate information on two or more epigenetic traits. These epigenetic data can facilitate correlation analysis between different traits. Advances in these technologies and information will provide opportunities to establish novel epigenetic markers and their functions in different types of tissue, development, and disease states.

ACKNOWLEDGMENTS

This work was supported by the 2021 Research Fund of the University of Seoul.

AUTHOR CONTRIBUTIONS

U.K. and D.S.L. wrote the manuscript.

CONFLICT OF INTEREST

The authors have no potential conflicts of interest to disclose.

Figures

Go to
Fig. 1.Overview of epigenomic features and single cell profiling techniques. sc, single-cell; sn, single-nucleus; Hi-C, high-throughput chromosome conformation capture; ChIP-seq, chromatin immunoprecipitation followed by sequencing; ChIC-seq, chromatin immunocleavage followed by sequencing; ChIL-seq, chromatin integration labelling sequencing; CUT&RUN, cleavage under targets and release using nucleasee; CUT&TAG, cleavage under targets and tagmentation; ATAC-seq, assay for transposase-accessible chromatin sequencing; DNase-seq, DNase I hypersensitive site sequencing; MNase-seq, micrococcal nuclease sequencing; RRBS, reduced representation bisulfite sequencing; BS-seq, bisulfite sequencing; PBAT, post-bisulfite adapter-tagging; 5mC, 5-methylcytosine; 5hmC, 5-hydroxymethylcytosine; 5fC, 5-fluorocytosine.
Fig. 2.Gene regulation of histone modifications.
Fig. 3.DNA methylation and modifying enzymes.
Fig. 4.Single-cell epigenome profiling techniques.

Tables

Methods for profiling epigenetic traits

Data type Methods Reference
Histone modification ChIP-seq (Barski et al., 2007)
CUT&TAG (Kaya-Okur et al., 2019)
CUT&RUN (Skene and Henikoff, 2017)
DNA methylation BS-seq (Cokus et al., 2008)
RRBS (Meissner et al., 2005)
MeDIP-seq (Weber et al., 2005)
Chromatin contact Hi-C (Lieberman-Aiden et al., 2009)
ChIA-PET (Wei et al., 2006)
Hi-ChIP (Mumbach et al., 2016)

Epigenetic changes and associated proteins

Epigenetic modification Associated protein Function Reference
Maintenance DNA methylation DNMT1 Maintain the pattern of DNA methylation (Klein et al., 2011)
De novo DNA methylation DNMT3A, DNMT3B Methylation of unmodified DNA (Spencer et al., 2017)
DNA demethylation TET1, TET2, TET3 Remove methylation (Ponciano-Gómez et al., 2017)
Histone acteylation p300/CBP Transcription activation (Benton et al., 2017)
Histone deacetylation HDACs Transcriptional regulation (Li and Seto, 2016)
H3K4 methylation SET1 Transcription activation (Zaidi et al., 2013)
H3K9 methylation EZH2, G9a/GLP Transcription repression (Iacono et al., 2018)
H3K27 methylation PRC2 Transcription repression (H3K27me1 is associated with transcription activiation) (Huang et al., 2021)
H3K79 methylation DOT1L Transcription activation (Johnson et al., 2009)
RNA methylation METTL3, METTL14, WTAP Installation of m6A on RNA residue (Ma et al., 2017)
YTHDF1/2/3, YTHDC1 Binding with m6A (Paris et al., 2019)
RNA demethylation FTO, ALKBH5 Remove of m6A on RNA residue (Zhang et al., 2016)

Multimodal omics techniques

Methods Profiling features Reference
DR-seq Genome, transcriptome (Dey et al., 2015)
G&T-seq Genome, transcriptome (Macaulay et al., 2015)
scTrio-seq Genome, transcriptome (Hou et al., 2016)
SIDR-seq Genome, transcriptome (Han et al., 2018)
CORTAD-seq Genome, transcriptome (Kong et al., 2019)
TARGET-seq Genome, transcriptome (Rodriguez-Meira et al., 2019)
PEA/STA Transcriptome, proteome (Genshaft et al., 2016)
PLAYR Transcriptome, proteome (Frei et al., 2016)
Abseq Transcriptome, proteome (Shahi et al., 2017)
CITE-seq Transcriptome, proteome (Stoeckius et al., 2017)
REAP-seq Transcriptome, proteome (Peterson et al., 2017)
RAID Transcriptome, proteome (Gerlach et al., 2019)
ECCITE-seq Transcriptome, proteome (Mimitou et al., 2019)
sci-CAR Chromatin accessibility, transcriptome (Cao et al., 2018)
T-ATAC-seq Chromatin accessibility, transcriptome (Satpathy et al., 2018)
scCAT-seq Chromatin accessibility, transcriptome (Liu et al., 2019)
SNARE-seq Chromatin accessibility, transcriptome (Chen et al., 2019)
ATAC-RNA-seq Chromatin accessibility, transcriptome (Reyes et al., 2019)
Paired-seq Chromatin accessibility, transcriptome (Zhu et al., 2019)
scMT-seq DNA methylome, transcriptome (Hu et al., 2016)
scM&T-seq DNA methylome, transcriptome (Angermueller et al., 2016)
sc-GEM DNA metyhlome, transcriptome (Cheow et al., 2016)
scNMT-seq Chromatin accessibility, DNA methylome, transcriptome (Clark et al., 2018)
scChaRM-seq Chromatin accessibility, DNA methylome, transcriptome (Yan et al., 2021)
scNOMeRe-seq Chromatin accessibility, DNA methylome, transcriptome (Wang et al., 2021)
snmCAT-seq Chromatin accessibility, DNA methylome, transcriptome (Luo et al., 2022)
DART-seq Transcriptome, RNA methylome (Meyer, 2019)
ORCA Transcriptome, chromatin conformation (Mateo et al., 2019)

Fig 1.

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Figure 1.Overview of epigenomic features and single cell profiling techniques. sc, single-cell; sn, single-nucleus; Hi-C, high-throughput chromosome conformation capture; ChIP-seq, chromatin immunoprecipitation followed by sequencing; ChIC-seq, chromatin immunocleavage followed by sequencing; ChIL-seq, chromatin integration labelling sequencing; CUT&RUN, cleavage under targets and release using nucleasee; CUT&TAG, cleavage under targets and tagmentation; ATAC-seq, assay for transposase-accessible chromatin sequencing; DNase-seq, DNase I hypersensitive site sequencing; MNase-seq, micrococcal nuclease sequencing; RRBS, reduced representation bisulfite sequencing; BS-seq, bisulfite sequencing; PBAT, post-bisulfite adapter-tagging; 5mC, 5-methylcytosine; 5hmC, 5-hydroxymethylcytosine; 5fC, 5-fluorocytosine.
Molecules and Cells 2023; 46: 86-98https://doi.org/10.14348/molcells.2023.0013

Fig 2.

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Figure 2.Gene regulation of histone modifications.
Molecules and Cells 2023; 46: 86-98https://doi.org/10.14348/molcells.2023.0013

Fig 3.

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Figure 3.DNA methylation and modifying enzymes.
Molecules and Cells 2023; 46: 86-98https://doi.org/10.14348/molcells.2023.0013

Fig 4.

Download
Figure 4.Single-cell epigenome profiling techniques.
Molecules and Cells 2023; 46: 86-98https://doi.org/10.14348/molcells.2023.0013

. Methods for profiling epigenetic traits.

Data typeMethodsReference
Histone modificationChIP-seq(Barski et al., 2007)
CUT&TAG(Kaya-Okur et al., 2019)
CUT&RUN(Skene and Henikoff, 2017)
DNA methylationBS-seq(Cokus et al., 2008)
RRBS(Meissner et al., 2005)
MeDIP-seq(Weber et al., 2005)
Chromatin contactHi-C(Lieberman-Aiden et al., 2009)
ChIA-PET(Wei et al., 2006)
Hi-ChIP(Mumbach et al., 2016)

. Epigenetic changes and associated proteins.

Epigenetic modificationAssociated proteinFunctionReference
Maintenance DNA methylationDNMT1Maintain the pattern of DNA methylation(Klein et al., 2011)
De novo DNA methylationDNMT3A, DNMT3BMethylation of unmodified DNA(Spencer et al., 2017)
DNA demethylationTET1, TET2, TET3Remove methylation(Ponciano-Gómez et al., 2017)
Histone acteylationp300/CBPTranscription activation(Benton et al., 2017)
Histone deacetylationHDACsTranscriptional regulation(Li and Seto, 2016)
H3K4 methylationSET1Transcription activation(Zaidi et al., 2013)
H3K9 methylationEZH2, G9a/GLPTranscription repression(Iacono et al., 2018)
H3K27 methylationPRC2Transcription repression (H3K27me1 is associated with transcription activiation)(Huang et al., 2021)
H3K79 methylationDOT1LTranscription activation(Johnson et al., 2009)
RNA methylationMETTL3, METTL14, WTAPInstallation of m6A on RNA residue(Ma et al., 2017)
YTHDF1/2/3, YTHDC1Binding with m6A(Paris et al., 2019)
RNA demethylationFTO, ALKBH5Remove of m6A on RNA residue(Zhang et al., 2016)

. Multimodal omics techniques.

MethodsProfiling featuresReference
DR-seqGenome, transcriptome(Dey et al., 2015)
G&T-seqGenome, transcriptome(Macaulay et al., 2015)
scTrio-seqGenome, transcriptome(Hou et al., 2016)
SIDR-seqGenome, transcriptome(Han et al., 2018)
CORTAD-seqGenome, transcriptome(Kong et al., 2019)
TARGET-seqGenome, transcriptome(Rodriguez-Meira et al., 2019)
PEA/STATranscriptome, proteome(Genshaft et al., 2016)
PLAYRTranscriptome, proteome(Frei et al., 2016)
AbseqTranscriptome, proteome(Shahi et al., 2017)
CITE-seqTranscriptome, proteome(Stoeckius et al., 2017)
REAP-seqTranscriptome, proteome(Peterson et al., 2017)
RAIDTranscriptome, proteome(Gerlach et al., 2019)
ECCITE-seqTranscriptome, proteome(Mimitou et al., 2019)
sci-CARChromatin accessibility, transcriptome(Cao et al., 2018)
T-ATAC-seqChromatin accessibility, transcriptome(Satpathy et al., 2018)
scCAT-seqChromatin accessibility, transcriptome(Liu et al., 2019)
SNARE-seqChromatin accessibility, transcriptome(Chen et al., 2019)
ATAC-RNA-seqChromatin accessibility, transcriptome(Reyes et al., 2019)
Paired-seqChromatin accessibility, transcriptome(Zhu et al., 2019)
scMT-seqDNA methylome, transcriptome(Hu et al., 2016)
scM&T-seqDNA methylome, transcriptome(Angermueller et al., 2016)
sc-GEMDNA metyhlome, transcriptome(Cheow et al., 2016)
scNMT-seqChromatin accessibility, DNA methylome, transcriptome(Clark et al., 2018)
scChaRM-seqChromatin accessibility, DNA methylome, transcriptome(Yan et al., 2021)
scNOMeRe-seqChromatin accessibility, DNA methylome, transcriptome(Wang et al., 2021)
snmCAT-seqChromatin accessibility, DNA methylome, transcriptome(Luo et al., 2022)
DART-seqTranscriptome, RNA methylome(Meyer, 2019)
ORCATranscriptome, chromatin conformation(Mateo et al., 2019)

References

  1. Angermueller C., Clark S.J., Lee H.J., Macaulay I.C., Teng M.J., Hu T.X., Krueger F., Smallwood S.A., Ponting C.P., and Voet T. (2016). Parallel single-cell sequencing links transcriptional and epigenetic heterogeneity. Nat. Methods 13, 229-232.
    Pubmed KoreaMed CrossRef
  2. Arita K., Isogai S., Oda T., Unoki M., Sugita K., Sekiyama N., Kuwata K., Hamamoto R., Tochio H., and Sato M. (2012). Recognition of modification status on a histone H3 tail by linked histone reader modules of the epigenetic regulator UHRF1. Proc. Natl. Acad. Sci. U. S. A. 109, 12950-12955.
    Pubmed KoreaMed CrossRef
  3. Back F. (1976). The variable condition of euchromatin and heterochromatin. Int. Rev. Cytol. 45, 25-64.
    Pubmed CrossRef
  4. Ball M.P., Li J.B., Gao Y., Lee J.H., LeProust E.M., Park I.H., Xie B., Daley G.Q., and Church G.M. (2009). Targeted and genome-scale strategies reveal gene-body methylation signatures in human cells. Nat. Biotechnol. 27, 361-368.
    Pubmed KoreaMed CrossRef
  5. Banaszynski L.A., Wen D., Dewell S., Whitcomb S.J., Lin M., Diaz N., Elsässer S.J., Chapgier A., Goldberg A.D., and Canaani E. (2013). Hira-dependent histone H3. 3 deposition facilitates PRC2 recruitment at developmental loci in ES cells. Cell 155, 107-120.
    Pubmed KoreaMed CrossRef
  6. Bannister A.J. and Kouzarides T. (2011). Regulation of chromatin by histone modifications. Cell Res. 21, 381-395.
    Pubmed KoreaMed CrossRef
  7. Barski A., Cuddapah S., Cui K., Roh T.Y., Schones D.E., Wang Z., Wei G., Chepelev I., and Zhao K. (2007). High-resolution profiling of histone methylations in the human genome. Cell 129, 823-837.
    Pubmed CrossRef
  8. Bartosovic M., Kabbe M., and Castelo-Branco G. (2021). Single-cell CUT&Tag profiles histone modifications and transcription factors in complex tissues. Nat. Biotechnol. 39, 825-835.
    Pubmed KoreaMed CrossRef
  9. Benton C.B., Fiskus W., and Bhalla K.N. (2017). Targeting histone acetylation: readers and writers in leukemia and cancer. Cancer J. 23, 286-291.
    Pubmed CrossRef
  10. Bird A., Taggart M., Frommer M., Miller O.J., and Macleod D. (1985). A fraction of the mouse genome that is derived from islands of nonmethylated, CpG-rich DNA. Cell 40, 91-99.
    Pubmed CrossRef
  11. Bokar J.A., Shambaugh M.E., Polayes D., Matera A.G., and Rottman F.M. (1997). Purification and cDNA cloning of the AdoMet-binding subunit of the human mRNA (N6-adenosine)-methyltransferase. RNA 3, 1233-1247.
    Pubmed KoreaMed
  12. Bose P., Dai Y., and Grant S. (2014). Histone deacetylase inhibitor (HDACI) mechanisms of action: emerging insights. Pharmacol. Ther. 143, 323-336.
    Pubmed KoreaMed CrossRef
  13. Briggs S.D., Bryk M., Strahl B.D., Cheung W.L., Davie J.K., Dent S.Y., Winston F., and Allis C.D. (2001). Histone H3 lysine 4 methylation is mediated by Set1 and required for cell growth and rDNA silencing in Saccharomyces cerevisiae. Genes Dev. 15, 3286-3295.
    Pubmed KoreaMed CrossRef
  14. Buenrostro J.D., Giresi P.G., Zaba L.C., Chang H.Y., and Greenleaf W.J. (2013). Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, DNA-binding proteins and nucleosome position. Nat. Methods 10, 1213-1218.
    Pubmed KoreaMed CrossRef
  15. Cao J., Cusanovich D.A., Ramani V., Aghamirzaie D., Pliner H.A., Hill A.J., Daza R.M., McFaline-Figueroa J.L., Packer J.S., and Christiansen L. (2018). Joint profiling of chromatin accessibility and gene expression in thousands of single cells. Science 361, 1380-1385.
    Pubmed KoreaMed CrossRef
  16. Cao R., Wang L., Wang H., Xia L., Erdjument-Bromage H., Tempst P., Jones R.S., and Zhang Y. (2002). Role of histone H3 lysine 27 methylation in Polycomb-group silencing. Science 298, 1039-1043.
    Pubmed CrossRef
  17. Chen S., Lake B.B., and Zhang K. (2019). High-throughput sequencing of the transcriptome and chromatin accessibility in the same cell. Nat. Biotechnol. 37, 1452-1457.
    Pubmed KoreaMed CrossRef
  18. Cheow L.F., Courtois E.T., Tan Y., Viswanathan R., Xing Q., Tan R.Z., Tan D.S., Robson P., Loh Y.H., and Quake S.R. (2016). Single-cell multimodal profiling reveals cellular epigenetic heterogeneity. Nat. Methods 13, 833-836.
    Pubmed CrossRef
  19. Cheung W.L., Turner F.B., Krishnamoorthy T., Wolner B., Ahn S.H., Foley M., Dorsey J.A., Peterson C.L., Berger S.L., and Allis C.D. (2005). Phosphorylation of histone H4 serine 1 during DNA damage requires casein kinase II in S. cerevisiae. Curr. Biol. 15, 656-660.
    Pubmed CrossRef
  20. Clark S.J., Argelaguet R., Kapourani C.A., Stubbs T.M., Lee H.J., Alda-Catalinas C., Krueger F., Sanguinetti G., Kelsey G., and Marioni J.C. (2018). scNMT-seq enables joint profiling of chromatin accessibility DNA methylation and transcription in single cells. Nat. Commun. 9, 781.
    Pubmed KoreaMed CrossRef
  21. Clayton A.L., Hebbes T.R., Thorne A.W., and Crane-Robinson C. (1993). Histone acetylation and gene induction in human cells. FEBS Lett. 336, 23-26.
    Pubmed CrossRef
  22. Cokus S.J., Feng S., Zhang X., Chen Z., Merriman B., Haudenschild C.D., Pradhan S., Nelson S.F., Pellegrini M., and Jacobsen S.E. (2008). Shotgun bisulphite sequencing of the Arabidopsis genome reveals DNA methylation patterning. Nature 452, 215-219.
    Pubmed KoreaMed CrossRef
  23. Coulondre C., Miller J.H., Farabaugh P.J., and Gilbert W. (1978). Molecular basis of base substitution hotspots in Escherichia coli. Nature 274, 775-780.
    Pubmed CrossRef
  24. Cusanovich D.A., Daza R., Adey A., Pliner H.A., Christiansen L., Gunderson K.L., Steemers F.J., Trapnell C., and Shendure J. (2015). Multiplex single-cell profiling of chromatin accessibility by combinatorial cellular indexing. Science 348, 910-914.
    Pubmed KoreaMed CrossRef
  25. Dai Z.Y., Jin S.M., Luo H.Q., Leng H.L., and Fang J.D. (2021). LncRNA HOTAIR regulates anoikis-resistance capacity and spheroid formation of ovarian cancer cells by recruiting EZH2 and influencing H3K27 methylation. Neoplasma 68, 509-518.
    Pubmed CrossRef
  26. Dekker J., Rippe K., Dekker M., and Kleckner N. (2002). Capturing chromosome conformation. Science 295, 1306-1311.
    Pubmed CrossRef
  27. Deng S., Zhang J., Su J., Zuo Z., Zeng L., Liu K., Zheng Y., Huang X., Bai R., and Zhuang L. (2022). RNA m6A regulates transcription via DNA demethylation and chromatin accessibility. Nat. Genet. 54, 1427-1437.
    Pubmed CrossRef
  28. Dey S.S., Kester L., Spanjaard B., Bienko M., and Van Oudenaarden A. (2015). Integrated genome and transcriptome sequencing of the same cell. Nat. Biotechnol. 33, 285-289.
    Pubmed KoreaMed CrossRef
  29. Dhayalan A., Rajavelu A., Rathert P., Tamas R., Jurkowska R.Z., Ragozin S., and Jeltsch A. (2010). The Dnmt3a PWWP domain reads histone 3 lysine 36 trimethylation and guides DNA methylation. J. Biol. Chem. 285, 26114-26120.
    Pubmed KoreaMed CrossRef
  30. Dixon J.R., Selvaraj S., Yue F., Kim A., Li Y., Shen Y., Hu M., Liu J.S., and Ren B. (2012). Topological domains in mammalian genomes identified by analysis of chromatin interactions. Nature 485, 376-380.
    Pubmed KoreaMed CrossRef
  31. Downs J.A., Allard S., Jobin-Robitaille O., Javaheri A., Auger A., Bouchard N., Kron S.J., Jackson S.P., and Côté J. (2004). Binding of chromatin-modifying activities to phosphorylated histone H2A at DNA damage sites. Mol. Cell 16, 979-990.
    Pubmed CrossRef
  32. Du H., Zhao Y., He J., Zhang Y., Xi H., Liu M., Ma J., and Wu L. (2016). YTHDF2 destabilizes m6A-containing RNA through direct recruitment of the CCR4-NOT deadenylase complex. Nat. Commun. 7, 12626.
    Pubmed KoreaMed CrossRef
  33. Eram M.S., Bustos S.P., Lima-Fernandes E., Siarheyeva A., Senisterra G., Hajian T., Chau I., Duan S., Wu H., and Dombrovski L. (2014). Trimethylation of histone H3 lysine 36 by human methyltransferase PRDM9 protein. J. Biol. Chem. 289, 12177-12188.
    Pubmed KoreaMed CrossRef
  34. Felsenfeld G. (2014). A brief history of epigenetics. Cold Spring Harb. Perspect. Biol. 6, a018200.
    Pubmed KoreaMed CrossRef
  35. Flyamer I.M., Gassler J., Imakaev M., Brandão H.B., Ulianov S.V., Abdennur N., Razin S.V., Mirny L.A., and Tachibana-Konwalski K. (2017). Single-nucleus Hi-C reveals unique chromatin reorganization at oocyte-to-zygote transition. Nature 544, 110-114.
    Pubmed KoreaMed CrossRef
  36. Frei A.P., Bava F.A., Zunder E.R., Hsieh E.W., Chen S.Y., Nolan G.P., and Gherardini P.F. (2016). Highly multiplexed simultaneous detection of RNAs and proteins in single cells. Nat. Methods 13, 269-275.
    Pubmed KoreaMed CrossRef
  37. Fritsch L., Robin P., Mathieu J.R., Souidi M., Hinaux H., Rougeulle C., Harel-Bellan A., Ameyar-Zazoua M., and Ait-Si-Ali S. (2010). A subset of the histone H3 lysine 9 methyltransferases Suv39h1, G9a, GLP, and SETDB1 participate in a multimeric complex. Mol. Cell 37, 46-56.
    Pubmed CrossRef
  38. Fu Y., Jia G., Pang X., Wang R.N., Wang X., Li C.J., Smemo S., Dai Q., Bailey K.A., and Nobrega M.A. (2013). FTO-mediated formation of N6-hydroxymethyladenosine and N6-formyladenosine in mammalian RNA. Nat. Commun. 4, 1798.
    Pubmed KoreaMed CrossRef
  39. Fuks F., Burgers W.A., Brehm A., Hughes-Davies L., and Kouzarides T. (2000). DNA methyltransferase Dnmt1 associates with histone deacetylase activity. Nat. Genet. 24, 88-91.
    Pubmed CrossRef
  40. Geiman T.M., Sankpal U.T., Robertson A.K., Zhao Y., Zhao Y., and Robertson K.D. (2004). DNMT3B interacts with hSNF2H chromatin remodeling enzyme, HDACs 1 and 2, and components of the histone methylation system. Biochem. Biophys. Res. Commun. 318, 544-555.
    Pubmed CrossRef
  41. Genshaft A.S., Li S., Gallant C.J., Darmanis S., Prakadan S.M., Ziegler C.G., Lundberg M., Fredriksson S., Hong J., and Regev A. (2016). Multiplexed, targeted profiling of single-cell proteomes and transcriptomes in a single reaction. Genome Biol. 17, 188.
    Pubmed KoreaMed CrossRef
  42. Gerlach J., van Buggenum J.A., Tanis S.E., Hogeweg M., Heuts B.M., Muraro M.J., Elze L., Rivello F., Rakszewska A., and van Oudenaarden A. (2019). Combined quantification of intracellular (phospho-) proteins and transcriptomics from fixed single cells. Sci. Rep. 9, 1469.
    Pubmed KoreaMed CrossRef
  43. Guelen L., Pagie L., Brasset E., Meuleman W., Faza M.B., Talhout W., Eussen B.H., De Klein A., Wessels L., and De Laat W. (2008). Domain organization of human chromosomes revealed by mapping of nuclear lamina interactions. Nature 453, 948-951.
    Pubmed CrossRef
  44. Guo H., Zhu P., Wu X., Li X., Wen L., and Tang F. (2013). Single-cell methylome landscapes of mouse embryonic stem cells and early embryos analyzed using reduced representation bisulfite sequencing. Genome Res. 23, 2126-2135.
    Pubmed KoreaMed CrossRef
  45. Guo X., Wang L., Li J., Ding Z., Xiao J., Yin X., He S., Shi P., Dong L., and Li G. (2015). Structural insight into autoinhibition and histone H3-induced activation of DNMT3A. Nature 517, 640-644.
    Pubmed CrossRef
  46. Halušková J. (2010). Epigenetic studies in human diseases. Folia Biol. (Praha) 56, 83-96.
    Pubmed
  47. Han K.Y., Kim K.T., Joung J.G., Son D.S., Kim Y.J., Jo A., Jeon H.J., Moon H.S., Yoo C.E., and Chung W. (2018). SIDR: simultaneous isolation and parallel sequencing of genomic DNA and total RNA from single cells. Genome Res. 28, 75-87.
    Pubmed KoreaMed CrossRef
  48. Harada A., Maehara K., Handa T., Arimura Y., Nogami J., Hayashi-Takanaka Y., Shirahige K., Kurumizaka H., Kimura H., and Ohkawa Y. (2019). A chromatin integration labelling method enables epigenomic profiling with lower input. Nat. Cell Biol. 21, 287-296.
    Pubmed CrossRef
  49. Heintzman N.D., Stuart R.K., Hon G., Fu Y., Ching C.W., Hawkins R.D., Barrera L.O., Van Calcar S., Qu C., and Ching K.A. (2007). Distinct and predictive chromatin signatures of transcriptional promoters and enhancers in the human genome. Nat. Genet. 39, 311-318.
    Pubmed CrossRef
  50. Helm M. and Motorin Y. (2017). Detecting RNA modifications in the epitranscriptome: predict and validate. Nat. Rev. Genet. 18, 275-291.
    Pubmed CrossRef
  51. Holliday R. and Pugh J.E. (1975). DNA modification mechanisms and gene activity during development: developmental clocks may depend on the enzymic modification of specific bases in repeated DNA sequences. Science 187, 226-232.
    CrossRef
  52. Hotchkiss R.D. (1948). The quantitative separation of purines, pyrimidines, an d nucleosides by paper chromatography. J. Biol. Chem. 175, 315-332.
    Pubmed CrossRef
  53. Hou Y., Guo H., Cao C., Li X., Hu B., Zhu P., Wu X., Wen L., Tang F., and Huang Y. (2016). Single-cell triple omics sequencing reveals genetic, epigenetic, and transcriptomic heterogeneity in hepatocellular carcinomas. Cell Res. 26, 304-319.
    Pubmed KoreaMed CrossRef
  54. Howell C.Y., Bestor T.H., Ding F., Latham K.E., Mertineit C., Trasler J.M., and Chaillet J.R. (2001). Genomic imprinting disrupted by a maternal effect mutation in the Dnmt1 gene. Cell 104, 829-838.
    Pubmed CrossRef
  55. Hu Y., Huang K., An Q., Du G., Hu G., Xue J., Zhu X., Wang C.Y., Xue Z., and Fan G. (2016). Simultaneous profiling of transcriptome and DNA methylome from a single cell. Genome Biol. 17, 88.
    Pubmed KoreaMed CrossRef
  56. Huang H., Zhu Q., Jussila A., Han Y., Bintu B., Kern C., Conte M., Zhang Y., Bianco S., and Chiariello A.M. (2021). CTCF mediates dosage-and sequence-context-dependent transcriptional insulation by forming local chromatin domains. Nat. Genet. 53, 1064-1074.
    Pubmed KoreaMed CrossRef
  57. Huang Y., Su R., Sheng Y., Dong L., Dong Z., Xu H., Ni T., Zhang Z.S., Zhang T., and Li C. (2019). Small-molecule targeting of oncogenic FTO demethylase in acute myeloid leukemia. Cancer Cell 35, 677-691.e10.
    Pubmed KoreaMed CrossRef
  58. Iacono G., Dubos A., Méziane H., Benevento M., Habibi E., Mandoli A., Riet F., Selloum M., Feil R., and Zhou H., et al. (2018). Increased H3K9 methylation and impaired expression of Protocadherins are associated with the cognitive dysfunctions of the Kleefstra syndrome. Nucleic Acids Res. 46, 4950-4965.
    Pubmed KoreaMed CrossRef
  59. Irizarry R.A., Ladd-Acosta C., Wen B., Wu Z., Montano C., Onyango P., Cui H., Gabo K., Rongione M., and Webster M. (2009). The human colon cancer methylome shows similar hypo-and hypermethylation at conserved tissue-specific CpG island shores. Nat. Genet. 41, 178-186.
    Pubmed KoreaMed CrossRef
  60. Ito S., D'Alessio A.C., Taranova O.V., Hong K., Sowers L.C., and Zhang Y. (2010). Role of Tet proteins in 5mC to 5hmC conversion, ES-cell self-renewal and inner cell mass specification. Nature 466, 1129-1133.
    Pubmed KoreaMed CrossRef
  61. Jang K.H., Heras C.R., and Lee G. (2022). m6A in the signal transduction network. Mol. Cells 45, 435-443.
    Pubmed KoreaMed CrossRef
  62. Jenuwein T. and Allis C.D. (2001). Translating the histone code. Science 293, 1074-1080.
    Pubmed CrossRef
  63. Johnson A., Li G., Sikorski T.W., Buratowski S., Woodcock C.L., and Moazed D. (2009). Reconstitution of heterochromatin-dependent transcriptional gene silencing. Mol. Cell 35, 769-781.
    Pubmed KoreaMed CrossRef
  64. Jones B., Su H., Bhat A., Lei H., Bajko J., Hevi S., Baltus G.A., Kadam S., Zhai H., and Valdez R. (2008). The histone H3K79 methyltransferase Dot1L is essential for mammalian development and heterochromatin structure. PLoS Genet. 4, e1000190.
    Pubmed KoreaMed CrossRef
  65. Karg E., Smets M., Ryan J., Forné I., Qin W., Mulholland C.B., Kalideris G., Imhof A., Bultmann S., and Leonhardt H. (2017). Ubiquitome analysis reveals PCNA-associated factor 15 (PAF15) as a specific ubiquitination target of UHRF1 in embryonic stem cells. J. Mol. Biol. 429, 3814-3824.
    Pubmed CrossRef
  66. Kaya-Okur H.S., Wu S.J., Codomo C.A., Pledger E.S., Bryson T.D., Henikoff J.G., Ahmad K., and Henikoff S. (2019). CUT&Tag for efficient epigenomic profiling of small samples and single cells. Nat. Commun. 10, 1930.
    Pubmed KoreaMed CrossRef
  67. Kim M.J., Lee H.J., Choi M.Y., Kang S.S., Kim Y.S., Shin J.K., and Choi W.S. (2021). UHRF1 induces methylation of the TXNIP promoter and down-regulates gene expression in cervical cancer. Mol. Cells 44, 146-159.
    Pubmed KoreaMed CrossRef
  68. Kim T. and Buratowski S. (2009). Dimethylation of H3K4 by Set1 recruits the Set3 histone deacetylase complex to 5′ transcribed regions. Cell 137, 259-272.
    Pubmed KoreaMed CrossRef
  69. Kleer C.G., Cao Q., Varambally S., Shen R., Ota I., Tomlins S.A., Ghosh D., Sewalt R.G., Otte A.P., and Hayes D.F. (2003). EZH2 is a marker of aggressive breast cancer and promotes neoplastic transformation of breast epithelial cells. Proc. Natl. Acad. Sci. U. S. A. 100, 11606-11611.
    Pubmed KoreaMed CrossRef
  70. Klein C.J., Botuyan M.V., Wu Y., Ward C.J., Nicholson G.A., Hammans S., Hojo K., Yamanishi H., Karpf A.R., and Wallace D.C. (2011). Mutations in DNMT1 cause hereditary sensory neuropathy with dementia and hearing loss. Nat. Genet. 43, 595-600.
    Pubmed KoreaMed CrossRef
  71. Ko M., Huang Y., Jankowska A.M., Pape U.J., Tahiliani M., Bandukwala H.S., An J., Lamperti E.D., Koh K.P., and Ganetzky R. (2010). Impaired hydroxylation of 5-methylcytosine in myeloid cancers with mutant TET2. Nature 468, 839-843.
    Pubmed KoreaMed CrossRef
  72. Kong S.L., Li H., Tai J.A., Courtois E.T., Poh H.M., Lau D.P., Haw Y.X., Iyer N.G., Tan D.S.W., and Prabhakar S. (2019). Concurrent single-cell RNA and targeted DNA sequencing on an automated platform for comeasurement of genomic and transcriptomic signatures. Clin. Chem. 65, 272-281.
    Pubmed CrossRef
  73. Kouzarides T. (2007). Chromatin modifications and their function. Cell 128, 693-705.
    Pubmed CrossRef
  74. Ku W.L., Nakamura K., Gao W., Cui K., Hu G., Tang Q., Ni B., and Zhao K. (2019). Single-cell chromatin immunocleavage sequencing (scChIC-seq) to profile histone modification. Nat. Methods 16, 323-325.
    Pubmed KoreaMed CrossRef
  75. Kuzmichev A., Nishioka K., Erdjument-Bromage H., Tempst P., and Reinberg D. (2002). Histone methyltransferase activity associated with a human multiprotein complex containing the Enhancer of Zeste protein. Genes Dev. 16, 2893-2905.
    Pubmed KoreaMed CrossRef
  76. Lan F. and Shi Y. (2009). Epigenetic regulation: methylation of histone and non-histone proteins. Sci. China C Life Sci. 52, 311-322.
    Pubmed CrossRef
  77. Langemeijer S., Kuiper R.P., Berends M., Knops R., Aslanyan M.G., Massop M., Stevens-Linders E., van Hoogen P., van Kessel A.G., and Raymakers R.A. (2009). Acquired mutations in TET2 are common in myelodysplastic syndromes. Nat. Genet. 41, 838-842.
    Pubmed CrossRef
  78. Lee D.S., Luo C., Zhou J., Chandran S., Rivkin A., Bartlett A., Nery J.R., Fitzpatrick C., O'Connor C., and Dixon J.R. (2019). Simultaneous profiling of 3D genome structure and DNA methylation in single human cells. Nat. Methods 16, 999-1006.
    Pubmed KoreaMed CrossRef
  79. Lee D.S., Shin J.Y., Tonge P.D., Puri M.C., Lee S., Park H., Lee W.C., Hussein S.M., Bleazard T., and Yun J.Y. (2014). An epigenomic roadmap to induced pluripotency reveals DNA methylation as a reprogramming modulator. Nat. Commun. 5, 5619.
    Pubmed KoreaMed CrossRef
  80. Lee J., Song J.H., Park J.H., Chung M.Y., Lee S.H., Jeon S.B., Park S.H., Hwang J.T., and Choi H.K. (2023). Dnmt1/Tet2-mediated changes in Cmip methylation regulate the development of nonalcoholic fatty liver disease by controlling the Gbp2-Pparγ-CD36 axis. Exp. Mol. Med. 55, 143-157.
    Pubmed KoreaMed CrossRef
  81. Leonhardt H., Page A.W., Weier H.U., and Bestor T.H. (1992). A targeting sequence directs DNA methyltransferase to sites of DNA replication in mammalian nuclei. Cell 71, 865-873.
    Pubmed CrossRef
  82. Li A., Chen Y.S., Ping X.L., Yang X., Xiao W., Yang Y., Sun H.Y., Zhu Q., Baidya P., and Wang X. (2017). Cytoplasmic m6A reader YTHDF3 promotes mRNA translation. Cell Res. 27, 444-447.
    Pubmed KoreaMed CrossRef
  83. Li Y. and Seto E. (2016). HDACs and HDAC inhibitors in cancer development and therapy. Cold Spring Harb. Perspect. Med. 6, a026831.
    Pubmed KoreaMed CrossRef
  84. Lieberman-Aiden E., Van Berkum N.L., Williams L., Imakaev M., Ragoczy T., Telling A., Amit I., Lajoie B.R., Sabo P.J., and Dorschner M.O. (2009). Comprehensive mapping of long-range interactions reveals folding principles of the human genome. Science 326, 289-293.
    Pubmed KoreaMed CrossRef
  85. Liu J., Yue Y., Han D., Wang X., Fu Y., Zhang L., Jia G., Yu M., Lu Z., and Deng X. (2014). A METTL3-METTL14 complex mediates mammalian nuclear RNA N6-adenosine methylation. Nat. Chem. Biol. 10, 93-95.
    Pubmed KoreaMed CrossRef
  86. Liu L., Liu C., Quintero A., Wu L., Yuan Y., Wang M., Cheng M., Leng L., Xu L., and Dong G. (2019). Deconvolution of single-cell multi-omics layers reveals regulatory heterogeneity. Nat. Commun. 10, 470.
    Pubmed KoreaMed CrossRef
  87. Liu N. and Pan T. (2015). RNA epigenetics. Transl. Res. 165, 28-35.
    Pubmed KoreaMed CrossRef
  88. Lund E., Oldenburg A.R., and Collas P. (2014). Enriched domain detector: a program for detection of wide genomic enrichment domains robust against local variations. Nucleic Acids Res. 42, e92.
    Pubmed KoreaMed CrossRef
  89. Luo C., Liu H., Xie F., Armand E.J., Siletti K., Bakken T.E., Fang R., Doyle W.I., Stuart T., and Hodge R.D. (2022). Single nucleus multi-omics identifies human cortical cell regulatory genome diversity. Cell Genom. 2, 100107.
    Pubmed KoreaMed CrossRef
  90. Ma J.Z., Yang F., Zhou C.C., Liu F., Yuan J.H., Wang F., Wang T.T., Xu Q.G., Zhou W.P., and Sun S.H. (2017). METTL14 suppresses the metastatic potential of hepatocellular carcinoma by modulating N6‐methyladenosine‐dependent primary MicroRNA processing. Hepatology 65, 529-543.
    Pubmed CrossRef
  91. Macaulay I.C., Haerty W., Kumar P., Li Y.I., Hu T.X., Teng M.J., Goolam M., Saurat N., Coupland P., and Shirley L.M. (2015). G&T-seq: parallel sequencing of single-cell genomes and transcriptomes. Nat. Methods 12, 519-522.
    Pubmed CrossRef
  92. Maiti A. and Drohat A.C. (2011). Thymine DNA glycosylase can rapidly excise 5-formylcytosine and 5-carboxylcytosine: potential implications for active demethylation of CpG sites. J. Biol. Chem. 286, 35334-35338.
    Pubmed KoreaMed CrossRef
  93. Mateo L.J., Murphy S.E., Hafner A., Cinquini I.S., Walker C.A., and Boettiger A.N. (2019). Visualizing DNA folding and RNA in embryos at single-cell resolution. Nature 568, 49-54.
    Pubmed KoreaMed CrossRef
  94. Meissner A., Gnirke A., Bell G.W., Ramsahoye B., Lander E.S., and Jaenisch R. (2005). Reduced representation bisulfite sequencing for comparative high-resolution DNA methylation analysis. Nucleic Acids Res. 33, 5868-5877.
    Pubmed KoreaMed CrossRef
  95. Meyer K.D. (2019). DART-seq: an antibody-free method for global m6A detection. Nat. Methods 16, 1275-1280.
    Pubmed KoreaMed CrossRef
  96. Mikkelsen T.S., Ku M., Jaffe D.B., Issac B., Lieberman E., Giannoukos G., Alvarez P., Brockman W., Kim T.K., and Koche R.P. (2007). Genome-wide maps of chromatin state in pluripotent and lineage-committed cells. Nature 448, 553-560.
    Pubmed KoreaMed CrossRef
  97. Miller T., Krogan N.J., Dover J., Erdjument-Bromage H., Tempst P., Johnston M., Greenblatt J.F., and Shilatifard A. (2001). COMPASS: a complex of proteins associated with a trithorax-related SET domain protein. Proc. Natl. Acad. Sci. U. S. A. 98, 12902-12907.
    Pubmed KoreaMed CrossRef
  98. Mimitou E.P., Cheng A., Montalbano A., Hao S., Stoeckius M., Legut M., Roush T., Herrera A., Papalexi E., and Ouyang Z. (2019). Multiplexed detection of proteins, transcriptomes, clonotypes and CRISPR perturbations in single cells. Nat. Methods 16, 409-412.
    Pubmed KoreaMed CrossRef
  99. Miura F., Enomoto Y., Dairiki R., and Ito T. (2012). Amplification-free whole-genome bisulfite sequencing by post-bisulfite adaptor tagging. Nucleic Acids Res. 40, e136.
    Pubmed KoreaMed CrossRef
  100. Mohn F., Weber M., Rebhan M., Roloff T.C., Richter J., Stadler M.B., Bibel M., and Schübeler D. (2008). Lineage-specific polycomb targets and de novo DNA methylation define restriction and potential of neuronal progenitors. Mol. Cell 30, 755-766.
    Pubmed CrossRef
  101. Mumbach M.R., Rubin A.J., Flynn R.A., Dai C., Khavari P.A., Greenleaf W.J., and Chang H.Y. (2016). HiChIP: efficient and sensitive analysis of protein-directed genome architecture. Nat. Methods 13, 919-922.
    Pubmed KoreaMed CrossRef
  102. Nagano T., Lubling Y., Várnai C., Dudley C., Leung W., Baran Y., Mendelson Cohen N., Wingett S., Fraser P., and Tanay A. (2017). Cell-cycle dynamics of chromosomal organization at single-cell resolution. Nature 547, 61-67.
    Pubmed KoreaMed CrossRef
  103. Nan X., Ng H.H., Johnson C.A., Laherty C.D., Turner B.M., Eisenman R.N., and Bird A. (1998). Transcriptional repression by the methyl-CpG-binding protein MeCP2 involves a histone deacetylase complex. Nature 393, 386-389.
    Pubmed CrossRef
  104. Ng S., Yue W., Oppermann U., and Klose R. (2009). Dynamic protein methylation in chromatin biology. Cell. Mol. Life Sci. 66, 407-422.
    Pubmed KoreaMed CrossRef
  105. North J.A., Šimon M., Ferdinand M.B., Shoffner M.A., Picking J.W., Howard C.J., Mooney A.M., van Noort J., Poirier M.G., and Ottesen J.J. (2014). Histone H3 phosphorylation near the nucleosome dyad alters chromatin structure. Nucleic Acids Res. 42, 4922-4933.
    Pubmed KoreaMed CrossRef
  106. Okano M., Bell D.W., Haber D.A., and Li E. (1999). DNA methyltransferases Dnmt3a and Dnmt3b are essential for de novo methylation and mammalian development. Cell 99, 247-257.
    Pubmed CrossRef
  107. Okano M., Xie S., and Li E. (1998). Cloning and characterization of a family of novel mammalian DNA (cytosine-5) methyltransferases. Nat. Genet. 19, 219-220.
    Pubmed CrossRef
  108. Oki M., Aihara H., and Ito T. (2007). Role of histone phosphorylation in chromatin dynamics and its implications in diseases. Subcell. Biochem. 41, 319-336.
    Pubmed CrossRef
  109. Otani J., Nankumo T., Arita K., Inamoto S., Ariyoshi M., and Shirakawa M. (2009). Structural basis for recognition of H3K4 methylation status by the DNA methyltransferase 3A ATRX-DNMT3-DNMT3L domain. EMBO Rep. 10, 1235-1241.
    Pubmed KoreaMed CrossRef
  110. Pan X., Hong X., Li S., Meng P., and Xiao F. (2021). METTL3 promotes adriamycin resistance in MCF-7 breast cancer cells by accelerating pri-microRNA-221-3p maturation in a m6A-dependent manner. Exp. Mol. Med. 53, 91-102.
    Pubmed KoreaMed CrossRef
  111. Paris J., Morgan M., Campos J., Spencer G.J., Shmakova A., Ivanova I., Mapperley C., Lawson H., Wotherspoon D.A., and Sepulveda C. (2019). Targeting the RNA m6A reader YTHDF2 selectively compromises cancer stem cells in acute myeloid leukemia. Cell Stem Cell 25, 137-148.e6.
    Pubmed KoreaMed CrossRef
  112. Parthun M. (2007). Hat1: the emerging cellular roles of a type B histone acetyltransferase. Oncogene 26, 5319-5328.
    Pubmed CrossRef
  113. Patil D.P., Chen C.K., Pickering B.F., Chow A., Jackson C., Guttman M., and Jaffrey S.R. (2016). m6A RNA methylation promotes XIST-mediated transcriptional repression. Nature 537, 369-373.
    Pubmed KoreaMed CrossRef
  114. Peng W., Li J., Chen R., Gu Q., Yang P., Qian W., Ji D., Wang Q., Zhang Z., and Tang J. (2019). Upregulated METTL3 promotes metastasis of colorectal Cancer via miR-1246/SPRED2/MAPK signaling pathway. J. Exp. Clin. Cancer Res. 38, 393.
    Pubmed KoreaMed CrossRef
  115. Peterson V.M., Zhang K.X., Kumar N., Wong J., Li L., Wilson D.C., Moore R., McClanahan T.K., Sadekova S., and Klappenbach J.A. (2017). Multiplexed quantification of proteins and transcripts in single cells. Nat. Biotechnol. 35, 936-939.
    Pubmed CrossRef
  116. Ping X.L., Sun B.F., Wang L., Xiao W., Yang X., Wang W.J., Adhikari S., Shi Y., Lv Y., and Chen Y.S. (2014). Mammalian WTAP is a regulatory subunit of the RNA N6-methyladenosine methyltransferase. Cell Res. 24, 177-189.
    Pubmed KoreaMed CrossRef
  117. Piunti A. and Shilatifard A. (2016). Epigenetic balance of gene expression by Polycomb and COMPASS families. Science 352, aad9780.
    Pubmed CrossRef
  118. Pogo B., Allfrey V., and Mirsky A. (1966). RNA synthesis and histone acetylation during the course of gene activation in lymphocytes. Proc. Natl. Acad. Sci. U. S. A. 55, 805-812.
    Pubmed KoreaMed CrossRef
  119. Ponciano-Gómez A., Martínez-Tovar A., Vela-Ojeda J., Olarte-Carrillo I., Centeno-Cruz F., and Garrido E. (2017). Mutations in TET2 and DNMT3A genes are associated with changes in global and gene-specific methylation in acute myeloid leukemia. Tumor Biol. 39, 1010428317732181.
    Pubmed CrossRef
  120. Rea S., Eisenhaber F., O'Carroll D., Strahl B.D., Sun Z.W., Schmid M., Opravil S., Mechtler K., Ponting C.P., and Allis C.D. (2000). Regulation of chromatin structure by site-specific histone H3 methyltransferases. Nature 406, 593-599.
    Pubmed CrossRef
  121. Reyes M., Billman K., Hacohen N., and Blainey P.C. (2019). Simultaneous profiling of gene expression and chromatin accessibility in single cells. Adv. Biosyst. 3, 1900065.
    Pubmed KoreaMed CrossRef
  122. Rodriguez-Meira A., Buck G., Clark S.A., Povinelli B.J., Alcolea V., Louka E., McGowan S., Hamblin A., Sousos N., and Barkas N. (2019). Unravelling intratumoral heterogeneity through high-sensitivity single-cell mutational analysis and parallel RNA sequencing. Mol. Cell 73, 1292-1305.e8.
    Pubmed KoreaMed CrossRef
  123. Rotem A., Ram O., Shoresh N., Sperling R.A., Goren A., Weitz D.A., and Bernstein B.E. (2015). Single-cell ChIP-seq reveals cell subpopulations defined by chromatin state. Nat. Biotechnol. 33, 1165-1172.
    Pubmed KoreaMed CrossRef
  124. Roth S.Y., Denu J.M., and Allis C.D. (2001). Histone acetyltransferases. Annu. Rev. Biochem. 70, 81-120.
    Pubmed CrossRef
  125. Rowley M.J. and Corces V.G. (2018). Organizational principles of 3D genome architecture. Nat. Rev. Genet. 19, 789-800.
    Pubmed KoreaMed CrossRef
  126. Russler-Germain D.A., Spencer D.H., Young M.A., Lamprecht T.L., Miller C.A., Fulton R., Meyer M.R., Erdmann-Gilmore P., Townsend R.R., and Wilson R.K. (2014). The R882H DNMT3A mutation associated with AML dominantly inhibits wild-type DNMT3A by blocking its ability to form active tetramers. Cancer Cell 25, 442-454.
    Pubmed KoreaMed CrossRef
  127. Santos-Rosa H., Schneider R., Bannister A.J., Sherriff J., Bernstein B.E., Emre N., Schreiber S.L., Mellor J., and Kouzarides T. (2002). Active genes are tri-methylated at K4 of histone H3. Nature 419, 407-411.
    Pubmed CrossRef
  128. Satpathy A.T., Saligrama N., Buenrostro J.D., Wei Y., Wu B., Rubin A.J., Granja J.M., Lareau C.A., Li R., and Qi Y. (2018). Transcript-indexed ATAC-seq for precision immune profiling. Nat. Med. 24, 580-590.
    Pubmed KoreaMed CrossRef
  129. Saxonov S., Berg P., and Brutlag D.L. (2006). A genome-wide analysis of CpG dinucleotides in the human genome distinguishes two distinct classes of promoters. Proc. Natl. Acad. Sci. U. S. A. 103, 1412-1417.
    Pubmed KoreaMed CrossRef
  130. Schoenfelder S. and Fraser P. (2019). Long-range enhancer-promoter contacts in gene expression control. Nat. Rev. Genet. 20, 437-455.
    Pubmed CrossRef
  131. Schuhmacher M.K., Kudithipudi S., Kusevic D., Weirich S., and Jeltsch A. (2015). Activity and specificity of the human SUV39H2 protein lysine methyltransferase. Biochim. Biophys. Acta 1849, 55-63.
    Pubmed CrossRef
  132. Shahi P., Kim S.C., Haliburton J.R., Gartner Z.J., and Abate A.R. (2017). Abseq: ultrahigh-throughput single cell protein profiling with droplet microfluidic barcoding. Sci. Rep. 7, 44447.
    Pubmed KoreaMed CrossRef
  133. Skene P.J. and Henikoff S. (2017). An efficient targeted nuclease strategy for high-resolution mapping of DNA binding sites. Elife 6, e21856.
    Pubmed KoreaMed CrossRef
  134. Smallwood S.A., Lee H.J., Angermueller C., Krueger F., Saadeh H., Peat J., Andrews S.R., Stegle O., Reik W., and Kelsey G. (2014). Single-cell genome-wide bisulfite sequencing for assessing epigenetic heterogeneity. Nat. Methods 11, 817-820.
    Pubmed KoreaMed CrossRef
  135. Smith Z.D. and Meissner A. (2013). DNA methylation: roles in mammalian development. Nat. Rev. Genet. 14, 204-220.
    Pubmed CrossRef
  136. Song L. and Crawford G.E. (2010). DNase-seq: a high-resolution technique for mapping active gene regulatory elements across the genome from mammalian cells. Cold Spring Harb. Protoc. 2010, pdb.prot5384.
    Pubmed KoreaMed CrossRef
  137. Spellmon N., Holcomb J., Trescott L., Sirinupong N., and Yang Z. (2015). Structure and function of SET and MYND domain-containing proteins. Int. J. Mol. Sci. 16, 1406-1428.
    Pubmed KoreaMed CrossRef
  138. Spencer D.H., Russler-Germain D.A., Ketkar S., Helton N.M., Lamprecht T.L., Fulton R.S., Fronick C.C., O'Laughlin M., Heath S.E., and Shinawi M. (2017). CpG island hypermethylation mediated by DNMT3A is a consequence of AML progression. Cell 168, 801-816.e13.
    Pubmed KoreaMed CrossRef
  139. Stevens T.J., Lando D., Basu S., Atkinson L.P., Cao Y., Lee S.F., Leeb M., Wohlfahrt K.J., Boucher W., and O'Shaughnessy-Kirwan A. (2017). 3D structures of individual mammalian genomes studied by single-cell Hi-C. Nature 544, 59-64.
    Pubmed KoreaMed CrossRef
  140. Stoeckius M., Hafemeister C., Stephenson W., Houck-Loomis B., Chattopadhyay P.K., Swerdlow H., Satija R., and Smibert P. (2017). Simultaneous epitope and transcriptome measurement in single cells. Nat. Methods 14, 865-868.
    Pubmed KoreaMed CrossRef
  141. Strahl B.D. and Allis C.D. (2000). The language of covalent histone modifications. Nature 403, 41-45.
    Pubmed CrossRef
  142. Suraweera A., O'Byrne K.J., and Richard D.J. (2018). Combination therapy with histone deacetylase inhibitors (HDACi) for the treatment of cancer: achieving the full therapeutic potential of HDACi. Front. Oncol. 8, 92.
    Pubmed KoreaMed CrossRef
  143. Szabo Q., Donjon A., Jerković I., Papadopoulos G.L., Cheutin T., Bonev B., Nora E.P., Bruneau B.G., Bantignies F., and Cavalli G. (2020). Regulation of single-cell genome organization into TADs and chromatin nanodomains. Nat. Genet. 52, 1151-1157.
    Pubmed KoreaMed CrossRef
  144. Tachibana M., Sugimoto K., Nozaki M., Ueda J., Ohta T., Ohki M., Fukuda M., Takeda N., Niida H., and Kato H. (2002). G9a histone methyltransferase plays a dominant role in euchromatic histone H3 lysine 9 methylation and is essential for early embryogenesis. Genes Dev. 16, 1779-1791.
    Pubmed KoreaMed CrossRef
  145. Tahiliani M., Koh K.P., Shen Y., Pastor W.A., Bandukwala H., Brudno Y., Agarwal S., Iyer L.M., Liu D.R., and Aravind L. (2009). Conversion of 5-methylcytosine to 5-hydroxymethylcytosine in mammalian DNA by MLL partner TET1. Science 324, 930-935.
    Pubmed KoreaMed CrossRef
  146. Waddington C.H. (1942). The epigenotype. Endeavour 1, 18-20.
    Pubmed CrossRef
  147. Wang X., Zhao B.S., Roundtree I.A., Lu Z., Han D., Ma H., Weng X., Chen K., Shi H., and He C. (2015). N6-methyladenosine modulates messenger RNA translation efficiency. Cell 161, 1388-1399.
    Pubmed KoreaMed CrossRef
  148. Wang Y., Yuan P., Yan Z., Yang M., Huo Y., Nie Y., Zhu X., Qiao J., and Yan L. (2021). Single-cell multiomics sequencing reveals the functional regulatory landscape of early embryos. Nat. Commun. 12, 1247.
    Pubmed KoreaMed CrossRef
  149. Weber A.R., Krawczyk C., Robertson A.B., Kuśnierczyk A., Vågbø C.B., Schuermann D., Klungland A., and Schär P. (2016). Biochemical reconstitution of TET1-TDG-BER-dependent active DNA demethylation reveals a highly coordinated mechanism. Nat. Commun. 7, 10806.
    Pubmed KoreaMed CrossRef
  150. Weber M., Davies J.J., Wittig D., Oakeley E.J., Haase M., Lam W.L., and Schuebeler D. (2005). Chromosome-wide and promoter-specific analyses identify sites of differential DNA methylation in normal and transformed human cells. Nat. Genet. 37, 853-862.
    Pubmed CrossRef
  151. Wei C.L., Wu Q., Vega V.B., Chiu K.P., Ng P., Zhang T., Shahab A., Yong H.C., Fu Y., and Weng Z. (2006). A global map of p53 transcription-factor binding sites in the human genome. Cell 124, 207-219.
    Pubmed CrossRef
  152. Wei Y., Mizzen C.A., Cook R.G., Gorovsky M.A., and Allis C.D. (1998). Phosphorylation of histone H3 at serine 10 is correlated with chromosome condensation during mitosis and meiosis in Tetrahymena. Proc. Natl. Acad. Sci. U. S. A. 95, 7480-7484.
    Pubmed KoreaMed CrossRef
  153. Xu Z., Lee D.S., Chandran S., Le V.T., Bump R., Yasis J., Dallarda S., Marcotte S., Clock B., and Haghani N. (2022). Structural variants drive context-dependent oncogene activation in cancer. Nature 612, 564-572.
    Pubmed KoreaMed CrossRef
  154. Yan R., Gu C., You D., Huang Z., Qian J., Yang Q., Cheng X., Zhang L., Wang H., and Wang P. (2021). Decoding dynamic epigenetic landscapes in human oocytes using single-cell multi-omics sequencing. Cell Stem Cell 28, 1641-1656.e7.
    Pubmed CrossRef
  155. Yang X.J. and Seto E. (2008). Lysine acetylation: codified crosstalk with other posttranslational modifications. Mol. Cell 31, 449-461.
    Pubmed KoreaMed CrossRef
  156. Yuan W., Xu M., Huang C., Liu N., Chen S., and Zhu B. (2011). H3K36 methylation antagonizes PRC2-mediated H3K27 methylation. J. Biol. Chem. 286, 7983-7989.
    Pubmed KoreaMed CrossRef
  157. Zaidi S., Choi M., Wakimoto H., Ma L., Jiang J., Overton J.D., Romano-Adesman A., Bjornson R.D., Breitbart R.E., and Brown K.K. (2013). De novo mutations in histone-modifying genes in congenital heart disease. Nature 498, 220-223.
    Pubmed KoreaMed CrossRef
  158. Zhang C., Samanta D., Lu H., Bullen J.W., Zhang H., Chen I., He X., and Semenza G.L. (2016). Hypoxia induces the breast cancer stem cell phenotype by HIF-dependent and ALKBH5-mediated m6A-demethylation of NANOG mRNA. Proc. Natl. Acad. Sci. U. S. A. 113, E2047-E2056.
    Pubmed KoreaMed CrossRef
  159. Zhang Z., Theler D., Kaminska K.H., Hiller M., de la Grange P., Pudimat R., Rafalska I., Heinrich B., Bujnicki J.M., and Allain F.H.T. (2010). The YTH domain is a novel RNA binding domain. J. Biol. Chem. 285, 14701-14710.
    Pubmed KoreaMed CrossRef
  160. Zhao J., Li B., Ren Y., Liang T., Wang J., Zhai S., Zhang X., Zhou P., Zhang X., and Pan Y. (2021). Histone demethylase KDM4A plays an oncogenic role in nasopharyngeal carcinoma by promoting cell migration and invasion. Exp. Mol. Med. 53, 1207-1217.
    Pubmed KoreaMed CrossRef
  161. Zheng G., Dahl J.A., Niu Y., Fedorcsak P., Huang C.M., Li C.J., Vågbø C.B., Shi Y., Wang W.L., and Song S.H. (2013). ALKBH5 is a mammalian RNA demethylase that impacts RNA metabolism and mouse fertility. Mol. Cell 49, 18-29.
    Pubmed KoreaMed CrossRef
  162. Zhu C., Yu M., Huang H., Juric I., Abnousi A., Hu R., Lucero J., Behrens M.M., Hu M., and Ren B. (2019). An ultra high-throughput method for single-cell joint analysis of open chromatin and transcriptome. Nat. Struct. Mol. Biol. 26, 1063-1070.
    Pubmed KoreaMed CrossRef
Mol. Cells
Jun 30, 2023 Vol.46 No.6, pp. 329~398
COVER PICTURE
The cellular proteostasis network is adaptively modulated upon cellular stress, thereby protecting cells from proteostasis collapse. Heat shock induces the translocation of misfolded proteins and the chaperone protein HSP70 into nucleolus, where nuclear protein quality control primarily occurs. Nuclear RNA export factor 1 (green), nucleolar protein fibrillarin (red), and nuclei (blue) were visualized in NIH3T3 cells under basal (left) and heat shock (right) conditions (Park et al., pp. 374-386).
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