DOT1L interaction partner AF10 controls patterning of H3K79 methylation and RNA polymerase II to maintain cell identity

  1. Coral K. Wille
  2. Edwin N. Neumann
  3. Aniruddha J. Deshpande
  4. Rupa Sridharan

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Abstract

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  1. Version published to 10.1016/j.stemcr.2023.10.017
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    Reply to the reviewers

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    Referee #3

    Evidence, reproducibility and clarity

    see the "Significance" section.

    Significance

    This manuscript reports the role and mechanism for AF10 in inhibition of mouse somatic cell reprogramming. It is known that DOT1L inhibits somatic cell reprogramming. In this study, a number of known DOT1L-interacting proteins were examined for their role in this process. They found that only AF10 (MLLT10) plays a similar role in somatic reprogramming, i.e., deletion of AF10 promotes reprogramming of somatic cells into iPS cells. Experiments in combination with DOT1L inhibitors showed that AF10 functioned in the same pathway as DOT1L. Reprogramming with AF10 mutants revealed that the AF10-DOT1L interaction but not the binding of AF10 to unmodified H3K27 is critical for reprogramming and somatic cell identity. ChIP-seq showed that AF10 deletion caused an ESC-like pattern of H3K79me1 at house-keeping genes. The data supported the conclusions. It is well-written. This study provided mechanistic insights into the role of DOT1L-AF10 in maintaining somatic cell identity and inhibiting somatic cell reprogramming.

    Major:

    This study is very similar to the following publication as cited:

    Deniz Uğurlu-Çimen, Deniz Odluyurt, Kenan Sevinç, Nazlı Ezgi Özkan-Küçük, Burcu Özçimen, Deniz Demirtaş, Eray Enüstün, Can Aztekin, Martin Philpott, Udo Oppermann, Nurhan Özlü, Tamer T. Önder. (2021). AF10 (MLLT10) prevents somatic cell reprogramming through regulation of DOT1L-mediated H3K79 methylation. Epigenetics Chromatin 14, 32. https://doi.org/10.1186/s13072-021-00406-7.

    Both manuscripts were deposited in BioRxiv in December 2020. Clearly these were two independent studies. The methodology and conclusions are very similar.

    Minor:

    Fig. 1B. The Axis labels are too small.

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    Referee #2

    Evidence, reproducibility and clarity

    Summary

    In this manuscript, the authors investigated the role of AF10, a subunit of DOT1L histone-methyl transferase complex for writing H3K79me1-2-3 marks, in cellular reprogramming. Using siRNA-mediated knockdown and chemical inhibitors, the authors show that AF10, and DOT1L as a whole, are inhibitory to reprogramming of mouse embryonic fibroblast cells (MEF) to induced pluripotent cells (iPSC), suggesting that AF10 plays an important role in determination and changes in cell lineages. The authors also show that this effect of AF10 is not transcription mediated. Based on their ChIP experiments of H3K79me1,2,3 and RNA Pol II, the authors claim that the effect of AF10 is mediated by "changes in epigenome circuitry".

    Major comments

    1. The claim that AF10 and DOT1L inhibits reprogramming of MEF to iPSC is largely supported by authors' experiments. Mostly, the authors used expression levels of NANOG as a mark for pluripotency. While it is a well-documented mark, an orthogonal mark (such as colony morphology, embroid bodies, etc.) will increase the rigor and confidence. This is especially important in the context of testing something like DOT1L complex which plays important role in transcription.
    2. The data presented here largely supports the claim that AF10-mediated effect is not through transcription.
    3. The authors final model ¬- "negative feedback by RNA-PolII recruited DOT1L leading to ESC-like state" - is not supported by the data presented here.
      • For example, at line 295, the authors say that H3K79me1 pattern in ΔAF10 "resembles the H3K79me1 found in ESCs which are much more TSS-enriched for this modification compared to MEFs." However, the data in 5H show that the pattern in ESC matches more with AF10 fl than ΔAF10.
      • At line, 299, "given that AF10 deleted cells retain H3K79 methylation..". This statement highly contradicts data in 4B, 4C, 5G and 5H where it is shown that deletion of AF10 leads to substantial loss of H3K79me1,2.
      • While the authors showed there are changes in H3K79 methylation pattern upon AF10 deletion, its link to changes in iPSC reprogramming is not shown. The Pol II occupancy data, shown for WT MEFs and ESC, do not support any of part of this claim. Even further, there is no evidence for changes in Pol II occupancy levels upon AF10 deletion.
    4. How do authors reconcile that there is increased expression of AF10 in pluripotent cells (Fig. 1A and 1B) although it inhibits pluripotency?
    5. Line 341, "We do not find any evidence that H3K79me2 opposes spreading of H3K27me3 in reprogramming to iPSCs" seems to be an over-interpretation. The experiment just shows that inhibition of PRC does not change global H3K79me2 levels. A direct role of H3K79me2 on H3K27me3 is not tested here.
    6. Fig S1D shows that deletion of AF10 can have additional effect to inhibition of DOT1L. This is in contrast to most of the main figures, especially, fig 1E. Some comment about this discrepancy is warranted.

    Minor comments

    1. It might help the reader if authors put a schematic of reprogramming regimen for Fig. 1A.
    2. At line 146, the authors inference " ΔAF10 is estimated to contribute about 40% of the DOT1Li phenotype in reprogramming" is not clear. It may help the reader the reader if more information is provided for their analyses and interpretation.
    3. Line 324, a typo: it should be "AF10"
    4. Line 456, It might be better for readers if the authors report whether and how RT-qPCR was normalized to housekeeping genes etc.
    5. Line 582, It is not clear at what step human cells were spike in. Also the type of human cells should also be reported.
    6. At many places (e.g. Fig 1E, Fig S3D) authors seem to have used multiple t-tests. Please consider using something like ANOVA to avoid multiple t-test error.
    7. Fig 1E. It is commendable that authors show factor independent reprogramming. It will be helpful for readers if authors show number of days for OSKM-dependent and OSKM-independent growth in the schematic.
    8. Fig S1C is not clear as such. Please add more information in the figure or legends.

    Referees cross-commenting

    With regards to reviewer1's comments: I particularly agree with major points 1 and 2 that authors' current model regarding feedback regulation needs more evidence. The technical concerns regarding ChIP normalization, esp. point 5, are also well-warranted.

    With regards to rev3's comments: The major concern about another similar study is well-warranted. The authors may want to explicate compare and contrast their key inferences with the other study.

    Significance

    The present work provides good evidence that AF10-mediated H3K79me can contribute to cellular reprogramming independent of steady-state mRNA levels. However, I think that the manuscript falls short of providing the basis for it. The claim that it is through subtle changes in H3K79me patterns seems nebulous and unsupported by the data presented here. If the manuscript finds the mechanistic basis for AF10's role in cellular reprogramming, it will be of interest to readers in general epigenetics as well as clinical fields that use histone methyl transferase inhibitors for treating leukemia.

    I am not an expert in the field of cellular reprogramming; so, I may not be able to judge the merits or caveats of authors' reprogramming methods and analyses.

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    Referee #1

    Evidence, reproducibility and clarity

    Summary

    Inactivation of the histone methyltransferase DOT1L increases the efficiency of reprogramming somatic cells to included pluripotent stem cells. Recent studies have shown that loss of the DOT1L-interacting protein AF10 or disruption of the DOT1L-interacting domain (OMLZ) of AF10 phenocopies DOT1L inhibition in human cells. Here, Wille et al use a transgenic reprogrammable mouse model to study the role of AF10 in reprogramming of mouse somatic cells. Using a conditional AF10 deletion allele, loss of AF10 was found to partially phenocopy inhibition of DOT1L and evidence is provided that AF10 and DOT1L act in the same pathway. Elegant rescue experiments showed that loss the OMLZ domain is sufficient to abolish the programming-barrier function of AF10. In contrast to human cells, AF10 deletion had a minimal impact on mRNA expression during reprogramming. Analysis of H3K79me1/2 patterns showed that AF10 loss leads reduced H3K79me1/2 levels across the genome, and a redistribution of H3K79me1 at highly expressed genes from a peak in gene bodies to a peak downstream of the TSS. This pattern is similar to that seen in ESCs, in which DOT1L activity and overall methylation levels are lower compared to MEFs. These findings provide evidence for the model that the DOT1L-AF10 interaction is critical for efficient H3K79 methylation and for posing a reprogramming barrier. In the absence of AF10, DOT1L can still methylate histones at highly expressed genes, presumably due to interactions with RNA Pol II and transcription elongation factors, but its overall activity is reduced.

    Major points

    1. The quantitative ChIP-seq analyses of H3K79me1 and H3K79me2 in control and AF10 knock-out cells reveal interesting patterns. In MEFs, H3K79me2 peaks at TSSs and H3K79me1 more in gene bodies, consistent with high DOT1L activity and conversion of H3K79me1 to H3K79me2 at TSSs. In ESCs, in which the nuclear DOT1L activity is much lower, H3K79me2 levels at the TSS are lower and H3KK79me1 levels at the TSS higher. AF10 loss during programming leads to a pattern similar to that found in ESCs. The authors suggest that 'deletion of AF10 is likely to enhance reprogramming by making the epigenome more ESC-like at predominantly housekeeping genes' (and Fig 6). This is an interesting hypothesis. However, the data is also consistent with an alternative and more-simple model that AF10 is needed to boost the catalytic activity of DOT1L and that partial loss of DOT1L activity upon loss of Af10 is sufficient to promote reprogramming. The latter model is supported by the observation that DOT1Li has dose-dependent effects and that loss of AF10 enhances reprogramming in combination with a range of DOT1Li concentrations and thus at a range of H3K79me1/2 levels (Figure S1). It would be useful to discuss different models side by side.
    2. In this context, the role of housekeeping genes also deserves attention. Line 276: 'Thus, the effect of AF10 deletion on promoting pluripotency occurs on genes that are commonly H3K79 methylated across cell types and not at specific lineage genes'. There is indeed a difference between highly and more lowly expressed genes but the causal relationship and role of housekeeping genes require further study. The data presented in this paper do not demonstrate that AF10 deletion affects pluripotency via genes that are commonly methylated by DOT1L. Therefore, without additional data, it seems too early to propose models of transcriptional feedback for biosynthetic/housekeeping genes (Discussion).
    3. For the ChIP-seq studies, a spike-in method is used to detect and take into account global differences in histone methylation. This method is based on the ChIP-Rx protocol of Orlando et al (2014). In the Orlando study, Drosophila chromatin was used for spike with the rationale that there is little homology between human/mouse and fly genome sequence, leading to minimal mapping of spike-in fly genome reads to the human/mouse genome. Here, the authors use mouse chromatin with a human chromatin spike-in. In the analysis method described (first mapping to the mouse genome and then aligning unmapped reads to the human genome), this potentially leads to mapping of human spike-in reads to the mouse genome. Even though the human spike in is only 1/53th of the total sample, the authors should adjust their ChIP analysis to avoid this issue. One possible solution is to generate a combined human-mouse reference genome, map unique reads, and then calculate the fraction of reads mapped to human and mouse. Alternatively, non-unique regions can be blacklisted.
    4. Related to the previous point, it is not clear to me how the scaling factor is calculated based on the numbers of Table. 1. The numbers given for the scaling factors do not seem to relate to the ratio of mouse/human reads. The authors should explain the scaling factor in more detail.
    5. H3K79me enrichment is calculated per gene body, normalized per kilobase of gene length. The authors should consider alternative metrics. While the method used is suitable for histone modifications that occur across the gene body, it might be less suitable or relevant for H3K79me, which predominantly occurs at the 5' end of transcribed gene bodies until it reaches internal exons (DOI 10.1038/nsmb.1924). Based on this distribution, normalizing per kilobase of gene length will lead to artificial lower enrichment scores for longer genes. Given the predominant localization of H3K79me at the 5' end of genes bodies, it seems more meaningful to calculate H3K79me enrichment in this region only instead of normalize per gene length.
    6. The label of Figure 1B is hard to read and the cell dots are hard to distinguish. Please increase font size and resolution. In this panel it is not clear to me whether the color indicates (graded) expression level or a more binary detection of transcripts? If the latter is the case, the signal (detection of a transcript in a single cell) might depend on the expression level of a transcript and the sequencing depth of each sample. Because of this uncertainty, it seems premature to speculate, based on single cell RNA-seq data, about variation in DOT1L complex formation. The authors should discuss this and take this into account in the analysis and representation of the data, or remove the panel and panel S1A.
    7. Several figure panels have very small fonts. Some of the text is not readable. The authors should increase the font size of these panels. Some of the legends are incomplete. Please explain all the abbreviations used in the legends.

    Minor points

    Figure 1D. Please explain the abbreviations in the legend.

    Figure 1E and 3F. Please explain the statistical test in the legend: e.g. tested against ff control. If the data was normalized to deltaAF10+DOT1Li, how was this condition taken along in the statistical test?

    Figure 1F. The line can be drawn this way across the datapoints but whether or not this is evidence for a linear relationship is not clear because the data points do not all follow the trend. More importantly, the added value of this analysis is not obvious. Clearly, a higher fraction of Af10-deleted cells is expected to lead to a higher fraction of cells with a programming phenotype associated with Af10 loss. I suggest that this panel is removed but that the relevant notion that near complete of Af10 loss contributes about 40% of the DOT1Li phenotype is maintained.

    Figure 3B/D. The pairing of the figure panels can lead to confusion. Empty vector refers to fl cells (black bar) as well as deltaAF10 cells (set to 100% and used as a reference; please add a dashed line at 100% with deltaAF10 label like in Fig. S3B), while the other constructs refer to deltaAF10 cells. To avoid confusion it would help to separate panel B and D and in panel D more clearly separate the fl cells from the deltaAF10 cells.

    Figure 3-4. Tubulin is used as a loading control for H3K79me1/2. A pan-histone H3 would be a more unambiguous control.

    Figure 4D. This panel shows changes in H3K79me1/2 ChIP-seq in DOT1Li treated vs control. Was this data normalized by the spike-in method? The samples are not mentioned in Table 1. The same question applies to the ESC vs MEF comparison.

    Figure 5B. It is not clear to what section of the bars the percentages next to the bars refer to.

    Figure 5D. Overlap of gene should be overlap of genes

    Figure 5G-H. Please explain the percentages in the legend.

    Figure S1B. Please explain the error bars and number of replicates.

    Figure S1D. The error bars refer to technical replicates. The authors should show biological replicates.

    Figure S2B. I could find a discussion in the text of the enriched motif of Cluster 7.

    Figure S3A. The axis labels are not readable. Please explain the two axes and the rationale for using this gate.

    Figure S3B. The authors should use SD instead of SEM.

    Significance

    This study builds on a growing body of work on the role of DOT1L in reprogramming of somatic cells. Recent studies point to a connection with the DOT1L-binding protein AF10 but the mechanisms, especially at the level of the epigenome, remained unclear. In general, very little is known about how DOT1L, its partners, and the methylation it deposits affect gene expression and cell fate.

    This study confirms that in mouse cells, similar to human cells, the DOT1L-interaction domain is involved in the reprogramming function of AF10. Importantly, in contrast to human cells, in the mouse model AF10 loss has minimal effect on gene expression, suggesting that alternative mechanisms must be involved. Focusing on the epigenome, and using a quantitative ChIP approach, the authors describe how H3K79me1 and H3K79me2 are affected by loss of AF10 and how this relates to gene expression and occupancy of RNA PolII. Although the precise mechanisms remain to be elucidated, the results provide an important basis for identifying the relevant molecular changes at the epigenome.

  10. Version published to 10.1101/2020.12.17.423347 on bioRxiv