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Reviewer #1: Partly

Reviewer #2: Partly

Reviewer #3: Yes

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Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

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Reviewer #2: Yes

Reviewer #3: Yes

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Reviewer #1: The manuscript revealed that, in ES cell, SF3B1K700E mutation increases expressoion of transcription regulators associated with hematopoiesis and immune genes. Based on that the SF3B1 gene is a component of the U2 splicing factor, the authors elucidated the molecular mechanisms underlying the abberant expression of genes in SF3B1K700E mutated ES cell and the SF3B1 mutation altered RNA polymeraseII elongation, resulting in the abberant expression of immune-related genes. I wrote several comments below.

The authors claimed that we established three independent heterozygous clones; however, they did not provide how single-cell cloning was performed. Did the authors validate the heterozygosity of those ES clones?

Did the authors observe significant p-values and ΔPSI% for candidate genes in Figure 1E? Were the candidate genes in Figure 1E observed within the volcano plots in Figure 1D?

As FDXR was not mentioned earlier in the manuscript, why was it selected for investigating in Figure 6B instead of the previously examined genes? What is the significance of the FDXR gene? Is it related to the immune gene sets?

The authors concluded that the functional impact of SF3B1 K700E is modulated by cellular state and the underlying genomic–transcriptomic background, based on contrasting mis-splicing patterns in ES cell with gene-expression profiles from bulk MDS patient samples. However, these represent fundamentally different cellular mixtures, an undifferentiated single clone versus a heterogeneous population of mature and progenitor blood cells. To support the conclusion, it would be better that the authors would compare SF3B1 K700E effects on ES cell with either that on CD34-positive hematopoietic progenitor cells from patients, iPSC-derived CD34-positive cells or MDS/AML cell lines that have the SF3B1 mutation.

Reviewer #2: The manuscript under review described a new hESC model of SF3B1-K700E mutation. This is an important model as this would be characterizing the functional impact of SF3B1 mutation in a non-cancer cell model context. The model will be useful in the splicing field to assess the impact of SF3B1-K700E in normal cellular context. In this note, the authors found mis-splicing patterns that were similar to reported publications. One interesting aspect is the increased in inflammation signature in hESC K700E cells, which is not seen in cancer/disease models reports. The alteration in RNA Pol 2 elongation has been reported. This would be just validation in a different model system, which will still important and informative.

Couple suggestions that would strengthen the paper overall.

1. General comment regarding GSEA result. The tables in main figures to show signficant pathways up or down are not very informative without the actual NES and statistical values here (eventhough there's a full supplemental table). It would be more informative to create some kind of heatmaps to represent the overall GSEA data as well. It is a bit difficult to know how strong the correlations are without going through the supplemental tables.

2. Major criticism: There seems to be a disconnect between the increased inflammation signature, alternative splicing, and transcription. Can the authors evaluate whether the increased in inflammatory signatures is due to changes in alternative splicing of those genes? Are there any correlation there?

- Second, are inflammatory gens that are differentially expressed in Sf3B1-K700E hESC corrected with where the authors saw increased in pause release by PRO-seq? Are there any correlation here?

3. CCR1 - the observation that CCR1 is downregulated in different cancer types is interestingly, Can the authors comment on why this is? (alternative splicing, gene expression).

Missing references

- Seiler et al - PMID: 29617667 - also identified reduced inflamation signature in pan-cancer analysis. This should be consistent with the findings here and should be included.

Reviewer #3: The authors consider the effects of the SF3B1 splicing mutation on the expression, splicing and transcription of embryonic stem cells. They use CRISPR/Cas9 to base edit three different lines. They show that there is some agreement between the gene expression differences they see, And those observed in patient samples. The main interesting, if slightly confusing, finding of the paper is that while in the stem cells they see up regulation of immune genes, in patient samples, they see it up regulation of the same gene sets. Additionally, they generate data to measure PolII occupancy and conclude that the mutant cells have reduced PolII pausing.

Overall, I think this is a strong well written paper that easily meets the bar for a PLOS one publication. There is substantial experimental and computational work that went into the findings. My main concerns are around some of the conclusions that are made when analyzing public bulk RNA sequencing data sets. The fundamental problem is that they mix together the effects of cell type and self state proportion changes with cell intrinsic expression changes. This is less of an issue for the stem cell data the authors generated because it's just the one type. Indeed, it is possible that the down regulation of immune genes seen in the patient samples could be a result of changes in cell type proportion as a result of the mutation rather than changes within a single cell type. There is in fact, single cell long read RNA sequencing data from patients with SF3B1 mutations which could be used to potentially address this question: Mariela Cortés-López et al. 2023 "Single-cell multi-omics defines the cell-type-specific impact of splicing aberrations in human hematopoietic clonal outgrowths". Similarly for the breast cancer data one has to consider whether it is changes in the immune response that result in the observed differences between S3B1 mutant and wild type cancers.

If this were a higher tier journal, I would certainly be asking for the authors to look at the data from the paper above and also to try to find single cell data for some of the other cancers considered. For PLOS one I don't know if this should be required: personally I would be OK with an acknowledgment of these limitations of the analysis.

Minor comments:

"negatively enriched" is an awkward term which sounds very similar to "depleted", which is not what the authors mean. I would suggest using "downregulated".

p12l300: "networks" there are no networks here (yet)

p14l365: how much of the DGE in BRCA/UVA is immune related (and compared to blood cancer?)

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<p>SF3B1K700E mutation in human embryonic stem cells causes aberrant expression of immune-related genes

PONE-D-25-20170R1

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