Functional impacts of 5-hydroxymethylcytosine, 5-formylcytosine, and 5-carboxycytosine at a single hemi-modified CpG dinucleotide in a gene promoter

Kitsera, Nataliya; Allgayer, Julia; Parsa, Edris; Geier, Nadine; Rossa, Martin; Carell, Thomas; Khobta, Andriy

doi:10.1093/nar/gkx718

Cited by 36 publications

(43 citation statements)

References 40 publications

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“…From our data, we found that at regions closest to the TSS (Up1 and FirstEx), both 5mC and 5hmC features correlated negatively with gene expression, although the correlation was stronger for 5mC ( Figure S8). This is consistent with a recent report that both types of DNA methylation could repress gene expression by affecting transcription factor binding at the promoter (Kitsera et al, 2017).…”

Section: Relationship Between Transcript Body Methylation and Expressionsupporting

confidence: 93%

New guidelines for DNA methylome studies regarding 5-hydroxymethylcytosine for understanding transcriptional regulation

Gao

et al. 2018

Preprint

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Many DNA methylome profiling methods cannot distinguish between 5-methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC). Since 5mC typically acts as a repressive mark whereas 5hmC is an intermediate form during active demethylation, the inability to separate their signals could lead to incorrect interpretation of the data. Meanwhile, many analysis pipelines quantify methylation level by the count or ratio of methylated reads, but the proportion of discordant reads ( analysis between matched tumor and normal pairs is particularly affected by the superposition of 5mC and 5hmC signals in WGBS data, with at least 25-40% of the differentially methylated regions (DMRs) identified from 5mC signals not detected from WGBS data. We do not find PDR to be more informative about expression levels than ratio of methylated reads, and integrating the two types of methylation features only improves the accuracy of inferred expression levels by at most 9.8%. Our results also confirm previous finding that methylation signals at transcript bodies are more indicative of gene expression levels than promoter methylation signals, and further show that in addition to the first exon, methylation signals at the last exon and internal introns also contain non-redundant information about gene expression. Overall, our study provides concrete data for evaluating the cost effectiveness of some experimental and analysis options in the study of DNA methylation in normal and cancer samples.

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Section: Relationship Between Transcript Body Methylation and Expressionsupporting

confidence: 93%

New guidelines for DNA methylome studies regarding 5-hydroxymethylcytosine for understanding transcriptional regulation

Gao

et al. 2018

Preprint

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“…S12). This is consistent with a recent report that both types of DNA methylation could repress gene expression by affecting transcription factor binding at the promoter (Kitsera et al 2017). Inside the transcript body, 5hmC tended to correlate more positively with gene expression than did 5mC in normal liver samples, but the reverse is observed for some liver and lung tumor samples.…”

Section: Relationship Between Transcript Body Methylation and Expressionsupporting

confidence: 92%

New guidelines for DNA methylome studies regarding 5-hydroxymethylcytosine for understanding transcriptional regulation

Gao

et al. 2019

Genome Res.

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Many DNA methylome profiling methods cannot distinguish between 5-methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC). Because 5mC typically acts as a repressive mark whereas 5hmC is an intermediate form during active demethylation, the inability to separate their signals could lead to incorrect interpretation of the data. Is the extra information contained in 5hmC signals worth the additional experimental and computational costs? Here we combine whole-genome bisulfite sequencing (WGBS) and oxidative WGBS (oxWGBS) data in various human tissues to investigate the quantitative relationships between gene expression and the two forms of DNA methylation at promoters, transcript bodies, and immediate downstream regions. We find that 5mC and 5hmC signals correlate with gene expression in the same direction in most samples. Considering both types of signals increases the accuracy of expression levels inferred from methylation data by a median of 18.2% as compared to having only WGBS data, showing that the two forms of methylation provide complementary information about gene expression. Differential analysis between matched tumor and normal pairs is particularly affected by the superposition of 5mC and 5hmC signals in WGBS data, with at least 25%–40% of the differentially methylated regions (DMRs) identified from 5mC signals not detected from WGBS data. Our results also confirm a previous finding that methylation signals at transcript bodies are more indicative of gene expression levels than promoter methylation signals. Overall, our study provides data for evaluating the cost-effectiveness of some experimental and analysis options in the study of DNA methylation in normal and cancer samples.

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“…[96] The discovery that the mammalian TDG enzyme removes fdC and cadC,c reates therefore the overarching idea that base excision repair and epigenetics are connected processes that allow regulation of transcriptional activity. [20,97] Another possibility is that fdC has independent epigenetic functions.T his would be in line with interaction data that revealed distinct reader proteins for hmdC and also fdC as well as cadC. [98,99] Of interest in this context are several analyses of genomic fdC profiles showing alink between the presence of fdC and epigenetic tuning at regulatory elements, such as enhancers and promoters.…”

Section: Hmdc Levels In Tumorsmentioning

confidence: 99%

Non‐canonical Bases in the Genome: The Regulatory Information Layer in DNA

et al. 2018

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Multicellular organisms developed the concept of specialized cells that perform specific functions. Examples are neurons and fibroblast to name just two out of more than 200. These cellular differences are established based on the same sequence information stored in the cell nucleus of all cells of an organism. The sequence information needs consequently different interpretations by the different cell types. During cellular development this interpretation of the genetic code has to be tightly regulated in space and time. Interpretation of the sequence information involves the controlled activation and silencing of specific genes so that certain proteins are made in one cell type but not in others. This involves an additional regulatory information layer beyond the pure base sequence. One aspect of this regulatory information layer relies on functional groups that are attached to the C(5) position of the canonical base dC. Currently four regulatory, non-canonical bases with a methyl (CH )-, a hydroxymethyl (CH OH)-, a formyl (CHO)- and a carboxyl (COOH)- group are known. While 5-methyl-cytidine is long recognised to be a regulatory base in the genome, the other three bases and the enzymes responsible for generating them, were just recently discovered.

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Functional impacts of 5-hydroxymethylcytosine, 5-formylcytosine, and 5-carboxycytosine at a single hemi-modified CpG dinucleotide in a gene promoter

Cited by 36 publications

References 40 publications

New guidelines for DNA methylome studies regarding 5-hydroxymethylcytosine for understanding transcriptional regulation

New guidelines for DNA methylome studies regarding 5-hydroxymethylcytosine for understanding transcriptional regulation

New guidelines for DNA methylome studies regarding 5-hydroxymethylcytosine for understanding transcriptional regulation

Non‐canonical Bases in the Genome: The Regulatory Information Layer in DNA

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