Peer review of: Distinct Cdk9-phosphatase switches act at the beginning and end of elongation by RNA (2020)

Reviewer #1 (Remarks to the Author): 

The work by Parua et all demonstrates a conserved role of distinct phosphatases that work on SPT5 at 
distinct steps of the transcription cycle. By combining in vitro phosphatase assays with in vivo 
distribution of transcriptional components following perturbation (by mutation or drug), this work 
makes a compelling case for further dissection of transcription elongation. As much as genomics is 
powerful, it is Figure 1 that is the highlight of the manuscript. Overall, it is a well thought out and well 
controlled piece that merits publication once minor questions are addressed. 

Minor points. 
55-74. The introduction is hard to follow in places in the last two paragraphs, but especially the one 
containing lines 55-74. I read it several times and could not quite grasp it. Is there a way to shorten 
it? 

84. Introduce the abbreviation in the Abstract for consistency? 

128. Higher sensitivity of Spt5 “CTD” phosphorylation compared to RPB1’s is intriguing. Flavopiridol 
has been shown in several systems to lead to a decrease in Ser2 phosphorylation. This is also stated 
in lines 194-195. Is this discrepancy due to technicalities (such as timing of treatment and the use of 
a more specific CDK9 inhibitor) or something else such as functional heterogeneity of Pol II Ser2p 
populations, differential requirements for CDK9 for Ser2 phosphorylation in different cells, etc? 

166-167. The sentence “Reactivity with Spt5…” may be correct technically, but it is not clear what to 
make of it in Supplementary Fig 2B. It seems to me that the effect of 806 substitution is not only 
modest (and may be should be quantified), but the IP datapoints do not appear to add useful 
information. 

Supplementary 2d and 2e. These appear to be shown in linear scale. Would it be better to show these 
in log scale? Secondly, I could not find information (which I may have missed) what signal was 
quantified for these plots: signal around genes or gene-agnostic data centric peaks? 

182. Principal component analysis is highly sensitive to normalization. Normalization is impossible to 
obtain for ChIP comparing different antibodies. PCA has limited use for samples (such as RNA-seq) 
that are highly similar and where normalization is straightforward, but it has no use for ChIP-seq. This 
panel should be removed. Perhaps clustering analysis that is less sensitive to normalization could be 
used? Overall, this panel does not add much to the manuscript anyway so deleting this will not harm 
it. 

212-214. Heatmaps of different versions of Spt5 are disjointed between figures 3 and 4. I understand 
that this is done to preserve the flow of the manuscript, but it possible to add a metagene plot 
overlapping the profiles of wild type and two mutants? It may be worthwhile to make the overlap plot 
a new 4A and move the orphan heatmap to supplementary, for example. 

Lines 221-230. Authors mention transcription induction of CDKN1A. Is transcriptional induction shown 
somewhere by RT-qPCR? I apologize in advance if I’d missed it. 

Lines 233-240. Along the same lines, what is happening to expression and ChIP-seq signal on genes 
that are not induced by P53 stabilization? 

Figure 5B. Metagene plots in 5B are not convincing along the vertical axis. Spike-in based 
normalization for ChIP-seq is impossible to very difficult with a notable exception of recombinant 
nucleosomes. A better figure would be to show the same metaplots, but for genes that are not 
upregulated by Nutlin. These must show less to no increase of light blue signal relatively to genes 
shown in 5b. This control is also essential. 

Figure 7a-c. The gene identity (MYC) is better to be labeled in the figure itself rather than only in a 
legend to 7B. It takes a moment to decipher that 7C probably shows MYC based on matching primer 
numbers. 

326. Should it be ‘marks’ (plural)? 

380-390. Because these are important statements, these should almost be placed to the beginning of 
discussion? 

392. Delete ‘Therefore’. 

512. Was Fisher formaldehyde regular or methanol-free that is sold in ampules? 

516. Specify the power number for Bioruptor? The high setting for ChIP is considered to be 140 if I 
recall correctly, but the instrument can go higher. 

Data handling. Which samples contained spike-ins? 

Data handling. How Sacharomyces spike-ins are helpful when added to immunoprecipitation 
reactions? The antibodies used will not recognize yeast proteins and will result in unknown and highly 
variable signal recovery for yeast read among samples that is likely driven by noise. 

Reviewer #2 (Remarks to the Author): 

Papua et al. address an interesting and important question in gene expression regulation by 
investigating how SPT5 phosphorylation varies across gene bodies. The authors previously showed in 
fission yeast that P-TEFb dependent SPT5 phosphorylations were lost at transcription termination sites 
through competition between the P-TEFb kinase and PP1 phosphatase. Here they have extended these 
studies to look at the role of various phosphatases during transcription elongation in human cells. The 
authors probe two different SPT5 phosphorylation sites, Ser666 and Thr806. They find that these 
phosphorylations are added and lost at different points during transcription. PP1 phosphatases are 
responsible for removing the phosphorylation on CTR-I at termination sites and PP4 phosphatase 
removes Ser666 phosphorylation at promoter-proximal sites. This paper is highly important because it 
shows that in addition to RNA polymerase II, specific sites on SPT5 are phosphorylated in response to 
its spatial location on a gene body. The study poses an enticing question as to whether other 
transcription elongation factors are regulated in a similar way. If true, this would provide an additional 
mechanism to carefully regulate spatial recruitment of additional factors to the elongation machinery. 
Overall, the manuscript is well written, and the data are clear. If some specific issues are addressed 
(see below), the reviewer fully supports publication of this important work in Nature Communications. 

Specific comments 
-Line 49: P-TEFb phosphorylates components of elongation and pausing complexes. The reviewer does 
not know of additional pausing factors that P-TEFb phosphorylates (NELF and DSIF are already 
mentioned). The authors should change “the paused complex” to “elongation factors”. 

-Line 128: The authors should cite the work of Matthias Geyer (2012 Czudnochowski et al., Nature 
Communications) where it was shown that P-TEFb is not a Ser2 kinase in vitro, specifically because 
the authors use P-TEFb in vitro in this work. 

-Supplementary Fig 1e: Not obvious that chromatin bound Thr806 phosphorylation level is changing in 
the PP1 depleted sample. It is also not clear that this blot is necessary given the other data in the 
manuscript. 

-Supplementary Fig 2a- Loading controls suggest that there is more GST-CTR1 input than the other 
peptides (significantly more). The authors comment in the legend that this is due to incomplete 
stripping of the membrane. This is a really important control, so it is advised the experiment is 
repeated and the sample is evenly split onto two gels/membranes to show the same amount of 
sample was indeed used, specifically because some faint bands appear on the phosphoblot for the 
other CTR constructs. The blots with the full-length protein look good. 

-Figure 2B: Are the ChIP plots scaled the same way? Add Y value to plots or state in figure legend that 
the scaling is the same. 

-Figure 2C, 3C: Plot the curves with the same Y axis boundaries to show the extent of differences. 

-Figure 3A, 4D, 7A S3A, S4 C, D: Mark termination sites or CPS sites on gene overview. There are 
probably multiple sites, but it helps to know where transcription may stop on a particular gene. 

-Figure 5C: Is it possible to comment on why Nutlin has a greater effect on non-paused genes? The 
model posited by the authors suggests that Ser666 phosphorylation follows pause release, and it 
would be naively thought that the effect of Nutlin would be greater on such genes. 

-Figure 7e: The authors see increased Pol II in the gene body when PP4R2 is depleted. This can come 
from enhanced transcription but can also arise from slow Pol II. If at all possible, the authors should 
investigate Pol II elongation rates in PP4R2 depleted cells using Gro-seq or TT-seq. This would confirm 
that enhanced Spt5 Ser666 phosphorylation leads to pause release and faster elongation rates. 

Minor comment 
-Supplementary Figure 3: Flip panel order so they match Figure 3.