Peer review of: Dynamic changes in the epigenomic landscape regulate human organogenesis and link to (2020)

Reviewers' Comments: 
 
Reviewer #1: 
Remarks to the Author: 
Dear authors, 
The manuscript “The epigenomic landscape regulating organogenesis in human embryos linked to 
developmental disorders” by Gerrard et al. provides unique insight regarding epigenetic landscape 
dynamics of H3K27Ac, H3K4me3 and H3K27me3 during a short period of human early 
development (CS14-CS22). Is very rare to have access to these early stages of human 
development. Moreover, the combination of human material accessibility and the epigenetic 
analysis used is unique to the Hanley lab and provides valuable information regarding this subject. 
 
Having said that, I think the paper would benefit from a clarification on the exact number of 
embryos used in a separate table mentioning what organs belong to each embryo and were used 
in what Chip-seq batch. 
 
Most importantly, I could not find information regarding the sex of the embryos used. This 
information is super important regarding the epigenetic marks, particularly H3K27me3, on the 
silent X chromosome in female embryos as that differs from male embryos. The embryos should 
be stratified by sex and the epigenetics of genes in the X chromosome analysed separately. 
If this is not possible, the sex of each embryo should be at least stated for each 
organ/batch/Chipseq. And regardless of whether it is possible to separately analyse the 3 
epigenetics marks in males and females, perhaps the epigenetic analysis of the genes on X 
chromosome should be considered separately from the autosomes not to cofound results. 
 
 
 
Reviewer #2: 
Remarks to the Author: 
In their manuscript, Gerrard et al. report the generation of a new dataset, profiling three different 
histone modifications across multiple organs during human organogenesis. This is a very useful 
resource that sheds light into a period of human development that remains understudied. The 
authors integrate this new dataset with previously generated RNA-seq data in order to explore the 
regulatory landscape of human organogenesis and reach several interesting conclusions: They 
cluster promoters according to the assayed features, finding limited evidence for the presence of 
bivalent promoters, identify differences in the mode of regulation between developmental 
transcription factors and organ-specific effector genes, and finally attempt to link the newly 
identified regulatory regions to human developmental disorders. 
 
Major concerns 
 
While the dataset is definitely impressive and will undoubtedly be very useful to the community, I 
find that the manuscript could benefit from more rigorous analyses that would consolidate some of 
the claims presented by the authors. Many of these claims are currently supported by limited and 
sometimes weak analyses. Specifically: 
 
1. In the first section focusing on promoters, the authors conclude that there is little evidence for 
promoter bivalency during human organogenesis. This is primarily based on their clustering 
analysis of promoter states. There are several concerns regarding this analysis:   
a. Clustering was performed using a too primarily oriented towards visualization and under default 
settings (more information should be provided on the precise parameters but in all available 
options the number of clusters seems to be determined by the user). Where is the evidence that 
the data can be optimally described by five clusters? Would it be possible that allowing for more 
clusters would reveal bivalent promoters as a subset of the repressed promoters (especially given 
the faint H3K4me3 signal observed in the repressed state)?   

b. This concern becomes even more relevant if one takes a closer look into Figure 3a. Actively 
repressed promoters clearly show a bimodal behaviour. Some remain repressed across all assayed 
tissues whereas others switch between the expressed and repressed state. Could this group 
correspond to bivalent promoters? An easy way to check would be to split the two groups (globally 
repressed vs facultative repressed and compare the H3K4me3 signal between the two groups). 
c. Furthermore, since bivalent promoters are primarily described based on the co-occurrence of 
H3K4me3 and H3K27me3, it might be informative to additionally perform the clustering only 
considering these two modifications (and allowing for four or more clusters). H3K27ac and active 
transcription are not expected to be found in bivalent promoters so they are not particularly 
informative for this particular question but their presence might distort the clustering analysis.    
 
2. In the last part of the manuscript, the authors intersect their putative enhancer annotation with 
a set of non-coding regions previously identified to be involved in developmental disorders. They 
then show that ~50% of noncoding de novo mutations fall within an active chromatin region. This 
is not surprising as these regions were previously selected for being conserved or for showing 
evidence of enhancer activity (experimentally validated or putative enhancers). A key step towards 
associating these mutations with the respective developmental phenotype would be to show that 
they are active in the organ that is most relevant to the respective disorder (i.e. neuronal organ 
for neurodevelopmental disorders and heart for heart defects). Surprisingly, with the exception of 
the single anecdotal case presented in Figure 7a, the authors don’t attempt to associate organ-
specific regulatory activity with the observed phenotype for each DNM. Even in Figure 6d it seems 
that they test for enrichment of their entire H3K27ac set against different phenotypes (although I 
cannot be sure as this analysis is not properly documented in the methods). 
 
3. The authors should provide more information regarding their ChIP-seq to RNA-seq correlation 
analysis. This is briefly mentioned in the results section and is almost entirely absent from the 
methods. Which correlation metric was used? Did the authors correct for the effect of spurious 
correlations due to multiple testing (for example by shuffling regulatory regions and genes from 
distant chromosomes)? How was the significance of the observed correlations estimated? 
Shouldn’t the results of this analysis be included in the Supplementary Material? This analysis cites 
Figure 7, which only presents data for one gene!   
 
Minor comments 
1. It’s quite alarming that some high rank patterns from the binary activity calling arise from 
combinations between single replicates of different organs (i.e. Fig. 5b upper limb/pancreas ranks 
6th, adrenal and heart is 8th). Do the authors attribute this to the biological samples or to the 
approach used for calling activity? Could it also be related to differences in the developmental 
stages of the samples (i.e. clustering of samples from different tissues but more similar 
developmental stages)? 
 
2. Regarding the transgenic zebrafish experiment: It’s not clear how sequence conservation in 
zebrafish was tested. Was this based on sequence only or was synteny also considered? The 
authors should state this in the methods. Scoring sequence conservation of non-coding elements 
over so long evolutionary distances is a difficult task and therefore absence of evidence for 
conservation should not be interpreted as evidence for its absence. Furthermore there is some 
ambiguity in the terms used by the authors (i.e. novel for previously unannotated, which could be 
confused with evolutionary novel; distance for evolutionary distance, which in the context of 
enhancer function could be confused with physical distance). I would therefore recommend 
rephrasing the concluding statements as something similar to this: “These data imply that our 
H3K27ac detection marks previously unannotated human enhancers, which function over 
considerable evolutionary distance despite the absence of detectable sequence conservation. This 
is likely associated with the overall conserved TF activity between homologous organs (Stergachis 
et al. Nature 2014)”. 
 
3. GO enrichments in temporal analysis: Not clear what the background is but it seems that all 

19,700 genes in Figure 3a were used. Since the point of the analysis is to identify differences 
between genes derepressed in the transition from pluripotency to organogenesis vs from 
organogenesis to adult organ, it’s more appropriate to limit the background set to genes expressed 
in the pancreas during any of the three stages. This might improve the resolution and remove 
confounders associated with general expression patterns in the pancreas (ex. involvement in 
diabetes). 
 
4. Overall, more information should be added to the methods section. The most critical issues 
were already highlighted above, but the authors could include more information in many sections 
(ex. parameters for MACS, STAR, read counting method, enrichment tests etc).   
 
 
 
Reviewer #3: 
Remarks to the Author: 
In this manuscript, Gerrard and colleagues mapped landscapes of histone H3K4me3, H3K27ac and 
H3K27me3 in thirteen tissues during human organogenesis. They classified discrete promoter 
states and identified a number of putative human embryo-enriched intergenic enhancers, several 
of which were validated in zebrafish. They further compared the promoter states and H3K27ac 
patterns across tissues. In addition, their analysis linked histone modification marked regions to de 
novo mutation sites which are associated with human developmental disorders. 
Characterizing the epigenomic patterns during organogenesis is important for understanding the 
mechanisms of human organ development in health and disease. However, the author's 
conclusions on the epigenome analysis of the entire organ are not convincing, and such analysis 
did not provide useful information and insights into our understanding of human organ 
development. For example, the fetal liver contains > 20 cell types, including endoderm-derived 
cells and mesoderm-derived cells. These mixed ChIP-seq signals are not suitable for identifying 
cell type-specific DNA regulatory sequences. The human epigenetic atlas should be established at 
the cell lineage level or at the single cell level, but not at the organ level.