Frequent lack of repressive capacity of promoter DNA methylation identified through genome-wide epigenomic manipulation

Abstract

It is widely assumed that the addition of DNA methylation at CpG rich gene promoters silences gene transcription. However, this conclusion is largely drawn from the observation that promoter DNA methylation inversely correlates with gene expression in natural conditions. The effect of induced DNA methylation on endogenous promoters has yet to be comprehensively assessed. Here, we induced the simultaneous methylation of thousands of promoters in the genome of human cells using an engineered zinc finger-DNMT3A fusion protein, enabling assessment of the effect of forced DNA methylation upon transcription, histone modifications, and DNA methylation persistence after the removal of the fusion protein. We find that DNA methylation is frequently insufficient to transcriptionally repress promoters. Furthermore, DNA methylation deposited at promoter regions associated with H3K4me3 is rapidly erased after removal of the zinc finger-DNMT3A fusion protein. Finally, we demonstrate that induced DNA methylation can exist simultaneously on promoter nucleosomes that possess the active histone modification H3K4me3, or DNA bound by the initiated form of RNA polymerase II. These findings suggest that promoter DNA methylation is not generally sufficient for transcriptional inactivation, with implications for the emerging field of epigenome engineering.

One Sentence Summary

Genome-wide epigenomic manipulation of thousands of human promoters reveals that induced promoter DNA methylation is unstable and frequently does not function as a primary instructive biochemical signal for gene silencing and chromatin reconfiguration.

PREreview of "Frequent lack of repressive capacity of promoter DNA methylation identified through genome-wide epigenomic manipulation"

This is a review of the preprint "Frequent lack of repressive capacity of promoter DNA methylation identified through genome-wide epigenomic manipulation" by Ethan Edward Ford, Matthew R. Grimmer, Sabine Stolzenburg, Ozren Bogdanovic, Alex de Mendoza, Peggy J. Farnham, Pilar Blancafort, and Ryan Lister.

The preprint was originally posted on bioRxiv on September 20, 2017 (DOI: https://doi.org/10.1101/170506).

Review

Despite being heavily studied, we still don't understand the exact consequences of DNA methylation on gene expression. There is a positive association between cytosine methylation (5mC) in gene bodies and their transcriptional status. On the other hand, regulatory regions such as promoters or enhancers tend to be negatively correlated with gene expression, with CG density playing an important role. Moreover, physiological processes such as imprinting, or pathologies such as cancer, indicate that CpG island (CGI) methylation is strongly associated with gene silencing. It remains to be answered whether 5mC is a cause or a consequence of such silencing.

The authors of this preprint approach this interesting question, particularly at the level of gene promoters. To this end, they took advantage of the off-target effects of a zinc finger (ZF)-DNMT3A fusion protein (shown in their Fig 1A, below) originally designed to target a GC-rich 18 bp sequence in the SOX2 promoter.

In addition to efficiently targeting SOX2 (34% increase in methylation after 3 days, half of it persistent after 9 days, and 2.5 fold decrease in mRNA) in MCF7 breast cancer cells, this fusion protein was able to bind 25142 off-target sites. This serendipitous finding enabled the genome-wide study of induced 5mC in regulatory regions using whole genome bisulfite sequencing (WGBS). Differential methylation was indeed found in more than 10K regions (DMRs) (by the way, it would be good to define DMR early in the text, in terms of size and number of CpG sites). It was not evident how the fusion protein selects its targets, considering that many were not CpG-rich regions, and why there is little overlap between protein binding sites and DMRs (35% as assessed by ChIP). Although the authors illustrate this in many ways, it may have been of interest to know the actual genomic distance between DMRs and the nearest ChIP peak.

Despite concerns about target affinity, this fusion protein efficiently induced 5mC (hypomethylation was almost absent). In addition, such induced 5mC was only partially associated with gene expression. In my view, one very interesting point of this work was that the authors included a "resting" condition, where 3-day doxycicline induction of ZF-DNMT3A was followed by 9 additional days w/o doxycicline. Using this strategy, they were able to show that most inducible 5mC is reversible, and especially at CpG-rich loci. Was there any difference in ZF-DNMT3A binding (or proximity) between "stable" and "reversible" DMRs?

DNA methylation can be lost trough passive dilution (i.e. DNMT1 impairment) or active removal (i.e. by TET dyoxigenases). Kinetics experiments (Fig 4B) are compatible with, approximately, half reduction of 5mC after each cell division, and therefore with the first option. The authors seem to rule out this possibility using cell cycle inhibitors. However, the evidence for this is less convincing. For example, the cell cycle profiles shown in Fig S4A do not indicate a strong synchronization. It is probably difficult to design such experiment, but a stronger effect may have been achieved with a mitotic arrest (e.g. nocodazol). In addition, it would have been relevant to see a positive control of passive demethylation, such as the one that may be obtained with 5-azacytidine. Finally, although the authors indirectly show TET activity (by 5hmC profiling), functional silencing of TETs would be a more relevant way to demonstrate that 5mC loss is an active process in their model. In my view, the presented data is not enough evidence to conclude that "induced DNA methylation is actively demethylated". As a side note, WGBS does not distinguish 5mC from 5hmC, so it is possible that 5mC loss after dox removal is underestimated. Indeed, ZF-DNMT3A would be a useful tool to also study the kinetics of other 5mC derivatives, such as 5fC and 5caC.

Additional information is provided in this study, in terms of active histone marks and initiated Pol II binding to DMRs. Together with the expression levels, this indicates that forced DNA methylation does not necessarily interfere with transcription. It is not clear if RNAseq data was of enough depth to also rule out differences at the level of isoform expression or alternative splicing events. This work also features a nice RNA-FISH strategy, used to rule out methylation mixed-response populations.

Other points include: RNAseq in Fig 1B is not described, there is no mention about association with H3K27ac (although data is shown), no description of treatment time on the legend to Fig S4, and no indication of time point for evaluating 5hmC kinetics. There is no clear indication of the number of replicates used in the WGBS experiment. Although technical validation is always important, if no or few replicates are included, a clear validation strategy should be stated.

Overall, this is a very interesting work, clearly presented and illustrated with attractive and informative visualizations. Although more work is needed to understand how 5mC stability is achieved, the authors correctly conclude that in their model DNA methylation itself is frequently insufficient to transcriptionally repress promoters. This information may prove highly useful for designing methylome-editing strategies.

Thanks again for posting this interesting work as a preprint,

Hector Hernandez-Vargas

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Frequent lack of repressive capacity of promoter DNA methylation identified through genome-wide epigenomic manipulation

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