Peer review of: ATAC-seq footprinting unravels kinetics of transcription factor binding during zygotic (2019)

REVIEWER COMMENTS 
 
Reviewer #1 (Remarks to the Author): 
 
In this study, Bentsen and colleagues introduce a new strategy (called TOBIAS) aimed at 
identifying footprints of chromatin-associated proteins from ATAC-seq accessibility profiles. They 
propose a data-driven correction of Tn5 bias and show that this is indeed increasing the signal-to-
noise at individual footprints, thereby improving the inference of transcription factor (TF) binding 
from combining footprints and sequence predictions. TOBIAS also provides unique features such as 
comparing TF-activities in chromatin across multiple conditions (not just pairwise) and 
reconstructing TF-TF networks based on the predicted genome-wide binding profiles of single TFs. 
Besides being considerably faster than other available tools, I find it crucial that TOBIAS has also 
been well packaged and documented (https://github.com/loosolab/TOBIAS). 
The authors first show that TOBIAS performs better than state-of-the-art tools, with the exception 
of msCentipede, to which TOBIAS performs comparably but at a fraction of the computational cost 
and the running time. The authors than used published data from both human and mouse ZGA to 
showcase the potential of TOBIAS to not only confirm previous observations but also to identify 
novel correlations in the data (such as those in Fig. 4e, 4h and 2c). 
I think TOBIAS will prove an extremely valuable and accessible tool to characterize the activities of 
transcription factors across different conditions and will very much benefit researchers in many 
fields that involve the study of transcriptional regulation and chromatin processes. I think the 
manuscript should be considered for publication in Nature Communications, as long as the authors 
are able to address some specific concerns (see bullet-points below). 
 
 
Major comments: 
 
- Despite not being an expert in the field, I appreciate the resource value of the manuscript to the 
community studying ZGA, so I was surprised the authors did not provide any easy way to access 
the predicted footprints genome-wide (for example as track hubs for the UCSC genome browser - 
one for human and one for mouse). Have I missed this? If not, I think the authors should consider 
setting this up. 
- Line 133: “TOBIAS generated a measurable footprint for 64% of the TFs (Supp. Figure 3e). This 
is in contrast to previous reports wherein it has been suggested that only 20% of all TFs leave 
measurable footprints”. This could be a very interesting observation, although fitting a two-
component model to the distribution shown in Suppl. Fig. 3e does not seem a strong estimate to 
distinguish “measurable” footprints from the rest. Can the authors provide a more robust estimate, 
separately for each TF, for the corrected footprint depth? (e.g. generating TF-specific null 
distributions of average footprints to then calculate the FDR of each estimate shown in the 
distribution). 
- The dynamic ranges of differences reported in transcriptional activities of many of the TFs in the 
human dataset (Suppl. Fig. 4 and Suppl. Table 2) are very small. Despite most of the inferences 
being made from these patterns of activity recapitulate previous knowledge in the field, when 
looking at specific instances (such as SALL4; lines 191-200) it is hard to evaluate if these 
differences are statistically significant. In the case of SALL4 for example, the on-off-on pattern 
might well be a flat one, given the absence of any assessment of variability for the activity scores 
in the current analysis. Can the authors provide an estimate of confidence intervals for these (and 
maybe all) activity scores, or at least explicitly discuss this limitation? The authors are making a 
strong case for this SALL4 observation in the Discussion, but I find the evidence supporting it 
rather weak. 
 
 
Minor comments: 
 
- Considering Suppl. Fig. 2a (and line 108): can the authors also provide panels showing 

quantifications of the footprint depths? Although these observations are formally supported by the 
results shown in Suppl. Fig. 2b-c, this would strengthen their initial statement about TOBIAS 
clearly outperforming the rest of tools. 
- With reference to this sentence from lines 208-209: “including several homeobox factors which 
already have described functions within ZGA” - can the authors specify the exact number of TFs 
(instead of “several”) and highlight the corresponding TF-genes in the figure panel? 
- I find it confusing that the authors first state that “The timing of ZGA varies between mice (2C) 
and humans (4C to 8C)” but then in Fig. 3 they focus the analyses on the 2C->4C transition in 
mouse and on the 8C->ICM in human. It seems that these comparisons are run to show “the 
ability of TOBIAS to capture differentially bound TFs, not only across the whole timeline, but also 
between individual conditions and species” but this is only mentioned after the analyses are 
introduced and commented. If this is the case, can the authors mention this beforehand? I think 
this would increase the clarity of the paragraph. 
- With reference to this paragraph “Footprinting (TOBIAS ScoreBigwig module)” (line 544 in the 
Methods section): considering the notation in the previous paragraph, would it be more 
appropriate to use c<sub>i</sub> instead of x<sub>i</sub> (corrected number of cuts instead 
of the total?) 
 
 
 
Reviewer #2 (Remarks to the Author): 
 
Over the last years it has become apparent that in the accessible 
regions from DNase-seq or ATAC-seq data one can see footprints of 
transcription factors. This technique is generally referred to a as 
digital genomic footprinting (DGF). The present manuscript introduces 
a pipeline ("TOBIAS") for DGF and applies this pipeline to analyze 
ATAC-seq data describing zygotic preimplantation development, based 
on publicly available data. 
 
The TOBIAS pipeline appears to produce qualitatively very good results. 
It is fast, and offers a number of useful features like differential 
binding and network construction. However, the manuscript suffers 
from numerous shortcomings. 
 
Firstly, the manuscript puts more emphasis on self-praise than on clarity of exposition. 
Even the first paragraph of the Results Section reads more like 
advertisement and does not convey much scientific information. 
The actual method behind TOBIAS is explained only inadequately. This reviewer 
spent quite some time studying Fig 1 which is where the method 
is supposed to be described (why is the overview of early embryonic development 
part of this figure?). Unfortunately, there is virtually no text 
to explain the extremely dense figure. The heart of the method seems to be 
what is depicted in part c, under "Bias correction and footprinting". 
What is the meaning of the insert to the left ("footprinting"), what is 
"Depth", what is the bottom image (where it says "threshold")? 
 
The authors stress that TOBIAS corrects for sequence bias introduced to 
ATAC-seq by the transposase. However, other programs also claim to correct 
for this, and therefore it would be interesting to structure the validation 
accordingly and dissect whether the present advance is due to 
better bias correction of due to some other novel feature of the footprinting. 
As it stands, this is impossible for the reader to discern. Fig. S2 claims 
it would clarify this, but there isn't even a discussion of Fig S2a. 
It pertains to two TFs. What about the others? Can one quantify this? 

 
S2b contains a group of distributions of auROC. The legend only says 
"auROC based on ENCODE ...". Which exact quantities are compared in the ROC curves? 
 
Other figures and figure legends suffer from a similar lack of explanation and discussion. 
 
The other novel features of TOBIAS appear useful but are not validated. 
Their proof is in the application to the ZGA data. 
 
 
 
The description of the methods as given under "The TOBIAS framework", lines 501 onward, 
is unclear. The formulae are cryptic due to the unconventional 
notation combining words (flank, mid, total, overlap, dist) and groups of 
letters (wf, wn, Wn?,...) . Needs clear notation, 
a sketch to illustrate the quantities, and/or a list of the different symbols. 
 
The analysis of the ZGA data is interesting, but follows the scheme of 
"We rediscover many known things therefore the rest of our findings also 
has to be true". The figures illustrating and supporting this analysis 
are again extremely dense and only superficially explained. 
 
The first section under Results should just be called "Validation of TOBIAS". 
Why "Classification and ..."? What does "classification" mean in this context? 
 
In summary, while TOBIAS is probably a good and useful tool, the manuscript 
fails in explaining the science behind it.