Peer review of: Transition to naïve human pluripotency mirrors pan-cancer DNA hypermethylation (2020)

Reviewers' Comments: 
 
Reviewer #1: 
Remarks to the Author: 
The authors show that prime to naive transition in human ES cells is associated with methylation 
of CpG islands for a group of developmental genes that are also methylated in cancers. The 
authors suggest this hypermethyaltion is potentially mediated by DNMT3A. The authors focus on 
transcription factors that are upregulated during early transition, and show by functional 
knockdown of factors that are upregulated that these factors may be involved in hypermethylation. 
 
The paper is very well communicated and the results are potentially interesting. A major 
interesting observation is that during the widespread hypomethylation associated with 
reprogramming to naive state, there is a group of genes getting hypermethylated. Molecular 
mechanisms that cause this hypermethylation, which the authors indicate, needs further 
investigation to link them conclusively to the hypermethylation involved during the whole 
transition from early, late and final naive state. Some of these concerns are elaborated in the 
comments below. 
 
- The model provides a good system to study if hypermethylation of these genes has functional 
consequences, which should be explored. 
 
- It has been shown recently (zhou et al. 2018, PMID: 29610480) that hypomethylation is linked 
to mitotic cell divisions, and within this context few regions get hypermethylated. The data in the 
current manuscript is interesting as the intermediate early and late transition stages involve rapid 
(is that correct?) hypmerthylation of many promoters followed by demethylation. These dynamics 
are very interesting, but the experimental designs do not address these dynamics through which 
the cells seem to traverse to the final naive state wherein fewer number of these CpG sites/regions 
ultimately. In the context of the Zhou et al model, is there a relation to mitotic cell divisions and 
appearance of the methylation changes? 
 
- Fig. 1b: How do early and late transition look for the majority of probes that get demethylated 
during primed to naive reprogramming? What are the numbers of CpGs acquiring methylation? 
How many of hypemethyalted sites are in CpG-islands, non-CpG-islands? 
 
- Fig. 1c: Does it suggest that during late transition these genes are hypermethylated and 
upregulated, but then again get downregulated and come to the same expression level as primed 
cells upon final transition to naive cells? This is counter-intuitive, and goes agains the mechanism 
that the authors propose. Like the authors suggest, could it be 5hmc increase in the late transition 
state, which then may acquire 5mC. Given this confounding observation, it becomes very 
important to map 5hmC to understand the biology. 
 
- Since different CpG probes are being considered in S4D and 3A, the effect of the KD cannot be 
easily discerned. Are there locus specific effects? Combined analyses/presentaiton (side by side) of 
the methylation changes at the different categories of differentially methylated CpGs (from early, 
late, naive vs. primed comparisons) in the different cell states (early, late, naive, primed) with the 
KDs will be required to understand role of each epigenetic enzyme, the state at which they active, 
and the locus affected. Currently there is little to make out from the way the data is analyzed 
(different probes are being analyzed in different figures). 
 
- The magnitude of the impact of DNMT3 KDs on naive state measured by alkaline phosphatase 
activity, although significant, is difficult to interpret if it alone is sufficient to monitor actual defect 
in reprogramming to naive state. For example, are differentiation and teratoma phenotypes 
altered? What happen to gene expression patterns between naive (with DNMT3A KD) and control 
naive cells? 
 

 
- In Fig. 3B, of the two different empty vector and TET1 samples (y-axis) correspond to early and 
primed? Is the data coming from the EPIC array? A previous study has shown that TET1 activity 
increases and DNMT3A activity decreases during primed -> naive transition (PMID: 28457889). 
The authors here suggest the opposite. Are these species differences some basic difference in the 
underlying epigenetic mechanisms? In regard if the TETs have any role, the down regulation of 
TET does not fit the observation that the naive cells globally have hypomethylation (even though 
there are some CpG islands that get hypermethylated). So then might there be a role for other 
TETs? For conclusive evidence for any role of TET1 (and other TET) requires studying TET1 
overexpression/KD through early, late to naive states. Further, to test if TET1 overexpression has 
any impact, it needs to be tested if TET1 overexertion causes hypomethylation in the primed cells. 
 
 
- Throughout the study, different definitions of hypermethylation (10%, 5%) used. Firstly, these 
differences are very marginal (especially 5%). Secondly, is it not better to use the same definition 
for consistency? From the heat plots, the beta-values seem very high for the regions analyzed. So 
why use such low differences? 
 
- The data for role of TFs in modulating hypermethylation is very interesting, and has been 
proposed by multiple studies (pioneered by Schübeler group, Gebhard et al. PMID: 20145141). 
The authors attribute TFs for directing hypermethyaltion in the said Cpg sites/regions. However, to 
rule out that these findings could be incidental, occupancy of the target regions by the TFs is 
required in control and the KD conditions for direct and conclusive evidence for their role in 
hypermethylation. Moreover, TF binding is generally believed to protect from DNA methylation 
(Schübeler group), however the data here suggest that these TFs are required for 
hypermethyaltion. Are the authors missing TFs that are critical as they focus on Tis that are 
overexpressed in there model? Moreover, TFs (expression levels) has been suggested to have 
minor consequences opposed to their recruitment efficacies. This issues should be considered and 
discussed. In this case, additional analyses is required to test if the CGI promoters studied here 
are prevented from silencing (and increase H3k4me3). 
 
 
 
Reviewer #2: 
Remarks to the Author: 
The manuscript of Patani et al. investigated the changes of DNA methylation during the resetting 
of primed hESCs into the naïve 2iLGo state using the NANOG/KLF2 dox-inducible transgenes. It is 
well known that this process results in a dramatic shift from a DNA hypermethylated primed state 
to a hypomethylated naïve state. The authors interrogated this process using Infinium 
MethylationEPIC array and mass spectrometry and focused in the hypemethylated sites. In 
principle this is refreshing and they were able to reveal hypermethylation patterns on the bivalent 
CGIs during the resetting, which is followed by identification of candidature transcription factors 
responsible for the dichotomy on the hypermethylation and subsequently they described that the 
same phenomena is also present in cancer. 
Although the study is interesting, it is somehow confusing, at points the data analysis and follow-
up experiments becomes convoluted or not properly performed to address the question. This in 
turn make the claims less convincing and rather confusing (I have tried to point out the main 
problems below). In my opinion, the manuscript has potential, but not only the concerns raised 
below need to be addressed, but also it needs to be made clear the main messages in a coherent 
narrative. 
I hope the following comments are of help to the authors: 
 
The authors utilized the system and protocol established by Takashima et al., 2014, did the 
authors check the degree of leakiness of the NANOG/KLF2 dox-inducible transgenes as this might 
affect the follow-up investigation of the mechanisms of bivalent CGI hypermethylation. 

 
In line 68-75, it is interesting that the authors looked into the hypermethylated CpGs during the 
resetting from primed to the naïve state, for example the HOXA cluster. It would be more 
informative if the authors can show the methylation of the same HOXA cluster of late transition 
+PKCi or –PKCi samples in figure 1c to support the claim that this is independent of PKCi. 
Why the authors have changed the way that they define a hypermethylated region (10% vs 5%) 
when whole-genome bisulfite-seq was analyzed is not clear. On this note, I believe that a 
correlation analysis rather than the presented enrichment analysis between the previously 
published data and their data set will be more informative and improve the conclusion on line 100. 
 
 
The conclusion that the hypermethylated genes are “attenuated” but “are characterised by low 
average expression in primed hESCs (Fig. 2b)” is interesting. However, I believe that the authors 
need to explore this more. Showing a boxplot is not enough….please break apart more the 
information as you did with the Hox genes. For example are these the bivalent domains, TFs?, 
show several examples, can you cluster them using the transcriptional dynamics or the 
methylation dynamics? 
 
On this note, the authors concluded that the HOX gene family becomes hypermethylated but are 
upregulated upon hESC reprogramming (Figure 2c), and the authors explained that this might be 
caused by the heterogeneity or 5-hydroxyMethyl-C. Would the authors be able to the assess the 
heterogeneity of their culture since its recently reported that naïve 2iLGo culture contains an 
intermediate subpopulation (Messmer et al., Cell reports, 2019).Also, why the comment in regards 
to 5-hydroxyMethyl-C? How hypermethylation can be confused with 5OH-Methyl-C? 
 
The rational for the experiments in figure 3 need to be better explained or not explained at all, 
since KD or OE epigenetic regulators (DNMTs or TETs) are expected to affect the methylation 
levels. Furthermore, it is difficult to understand figure 3 and the conclusion n from such 
experiments, e.g. why the effect of KD or OE of these regulators at the hypermethylated bivalent 
regions identified in figure 1 were not examined? 
The author suggested that the isoform DNMT3A2 is responsible for de novo DNA methylation 
based on the observation that isoform DNMT3A1 knockdown did not impact on the methylation. 
Has the author also conducted the knockdown of the isoform DNMT3A2? It would be better to 
show the results in parallel with the knockdown of DNMT3A1. 
 
The author mentioned that NANOG and KLF2 or the associated networks might be the factors 
coordinating the hypermethylation based on the observation that removal of MEK inhibitor or 
GSK3β inhibitor during reprogramming did not impact on the hypermethylation in Figure 5d. 
Indeed, Was not this expected? 
One of the key claims (abstract) is that NANOG is a key driver of the hypermethylation of bivalent 
regions but the presented results do not convincingly support this conclusion. Is there any 
experiment that can be done to more specifically consolidate the role of NANOG on 
hypermethylation in the context of primed to naïve resetting? 
 
The main message of this manuscript is that the hypermethylated bivalent regions identified 
during primed to naïve resetting can be found in cancer. The authors examined the link in one 
figure (figure 7). Again, I found this is not convincing. Not only the analysis lacks depth but the 
authors did not interrogate the mechanism at all. This would greatly strength the claims of the 
manuscript. 
 
 
Minor points: 
The introductory paragraph I not convincing, in the sense that it does not lead well to why this 
study was design to answer the “oncogenic” question. The sentence in line 46 is not enough. 
The authors might consider using ‘resetting’ ‘reversion’ ‘toggling’ instead of reprogramming for 

primed hESCs to naïve transition to avoid confusion. 
The statistical analyses is not clear at all times, neither much of the bioinformatic analysis and 
should include supplementary data for important analysis. 
 
Completely a minor point: The figures are call in lower case, eg. Figure 2b, however in the real 
figures, the figure is call in upper cases “B”