The c-Myc protooncogene places a demand on glucose uptake to drive glucose-dependent biosynthetic pathways. To meet this demand, c-Myc protein (Myc henceforth) drives the expression of glucose transporters, glycolytic enzymes, and represses the expression of thioredoxin interacting protein (TXNIP), which is a potent negative regulator of glucose uptake. A Mychigh/TXNIPlow gene signature is clinically significant as it correlates with poor clinical prognosis in triple-negative breast cancer (TNBC) but not in other subtypes of breast cancer, suggesting a functional relationship between Myc and TXNIP. To better understand how TXNIP contributes to the aggressive behavior of TNBC, we generated TXNIP null MDA-MB-231 (231:TKO) cells for our study. We show that TXNIP loss drives a transcriptional program that resembles those driven by Myc and increases global Myc genome occupancy. TXNIP loss allows Myc to invade the promoters and enhancers of target genes that are potentially relevant to cell transformation. Together, these findings suggest that TXNIP is a broad repressor of Myc genomic binding. The increase in Myc genomic binding in the 231:TKO cells expands the Myc-dependent transcriptome we identified in parental MDA-MB-231 cells. This expansion of Myc-dependent transcription following TXNIP loss occurs without an apparent increase in Myc’s intrinsic capacity to activate transcription and without increasing Myc levels. Together, our findings suggest that TXNIP loss mimics Myc overexpression, connecting Myc genomic binding and transcriptional programs to the nutrient and progrowth signals that control TXNIP expression. This study shows that genomic binding and transcriptional activation by the oncogene product Myc are controlled by Thioredoxin Interacting Protein (TXNIP), whose expression is in turn tightly linked to cellular energy status, thereby connecting Myc transcriptional activity to cell metabolism and nutrient status. Thioredoxin interacting protein (TXNIP) is an α-arrestin protein with several anti-proliferative functions, predominant among these are activities as a negative regulator of glucose uptake and as a suppressor of multiple progrowth signaling pathways –5. ConsiOur previous work demonstrated that low TXNIP expression correlates with poor clinical outcomes in TNBC, but not in other breast cancer subtypes . FurtherMyc is implicated in more than 50% of human malignancy with elevated levels of transcriptionally active Myc being critical for its oncogenic function . ElevateIn this report, we provide evidence that TXNIP loss drives a global increase in Myc genomic binding and drives gene expression programs enriched for known Myc targets. Surprisingly, this expansion of the Myc transcriptome was not accompanied by an increase in Myc protein expression, suggesting that TXNIP loss increases in Myc’s activity as a transcription factor. Our data support a model where TXNIP loss increases Myc’s capacity to bind its genomic targets, rather than increasing its intrinsic capacity to activate or repress transcription.p-value (pAdj) ≤0.05, we identified 1,050 and 742 genes whose expression was up- and down-regulated, respectively, in response to TXNIP deletion. INHBB, KISS1, FOXA2, and ZNF704 were among the most highly down-regulated genes, whereas AKR1C3, MT-ATP8, and G0S2 were the most highly up-regulated genes  Figs  and S1A.ed genes .To identify TXNIP-regulated pathways, we compared our 231:TKO dataset with annotated gene sets using preranked Gene Set Enrichment Analysis (GSEA) . Given tTo determine the generality of TXNIP loss on Myc-like gene signatures, we deleted it from 2 additional cell lines. First, we deleted TXNIP from HCC70 TNBC cells, which also have intermediate levels of Myc and TXNIP mRNA , and perTo determine whether the inverse relationship between TXNIP and Myc transcriptional programs is restricted to cell lines, we downloaded the gene expression data from 1,904 breast tumors annotated in the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) dataset . We thenBecause TXNIP loss in MDA-MB-231 cells leads increased the expression of known Myc targets, we next determined whether the changes in gene expression in the 231:TKO cells were Myc dependent. To do so, we reduced Myc levels using a short interfering RNA approach and performed RNA-seq on RNA isolated 48 hours after transfection of the siRNAs. We achieved robust Myc knockdown . FurtherTo begin to understand the functional outcome of the interplay between TXNIP and Myc, we next used mass spectrometry approaches to measure steady state metabolites in 231:TKO cells before and after Myc knockdown. TXNIP loss resulted in the up-regulation of multiple metabolites and the levels of the majority of these were reduced following Myc knockdown using an siRNA approach . These mFinally, to test the effect of TXNIP loss on orthotopic tumor growth in vivo, we transplanted parental 231 and 231:TKO cells into the cleared mammary fat pads of immunocompromised mice and used caliper measurements to monitor their growth over time. In this setting, we found, for approximately the first 5 weeks of the experiment, parental 231 and parental 231:TKO cells grew at the same rate. After this time, the parental 231 xenografts continued to grow; however, the growth of the 231:TKO cells slowed dramatically . At the TXNIP loss resulted in increased Myc-dependent gene expression programs, yet did not result in broad up-regulation of gene expression across the genome. These findings suggest that TXNIP loss might increase Myc transcriptional programs by a direct mechanism, rather than by an indirect mechanism that would derepress transcription genome-wide. Because TXNIP loss does not change Myc levels Figs , and S1CWe used ChIPseeker  to assocWe used Hypergeometric Optimization of Motif EnRichment (HOMER)  analysisBecause previous publications indicate that Myc can regulate different subgroups of targets based on the affinity of the Myc binding site ,28, we uWe next investigated the Myc- and TXNIP-dependent regulation of G0S2 as representative of their reciprocal function in gene regulation. We chose to examine G0S2 for 3 reasons: (1) it was among the most highly up-regulated genes in the 231:TKO cells  Figs; 2. Our MycTo investigate the role of the G0S2 promoter in mediating the effects of TXNIP loss further, we generated a luciferase reporter construct that contains 1,493 base pairs upstream of the G0S2 translational start site that encompass the Myc-occupied region identified in our ChIP experiments . This reTo examine the relationship between the Myc-dependent gene expression programs and increased Myc binding in 231:TKO cells, we compared the Myc-dependent transcripts identified in 231:TKO+siMyc cells with genes that showed increased Myc occupancy in 231:TKO cells. We found that 2,903 (51.2%) Myc-dependent genes identified in 231:TKO+siMyc cells showed increased Myc binding in the 231:TKO cells . These 2To better understand what constitutes a functional Myc binding event, we evaluated additional parameters. We found no correlation between the number of Myc sites and the magnitude of Myc-transcriptional regulation in either down- or up-regulated genes in 231:TKO+siMyc cells . FurtherTo understand whether the global Myc biding events in 231:TKO cells are conserved across other cell lineages, we compared our genomic Myc binding profiles with those from the U2OS osteosarcoma cell line  and the TXNIP loss led to a dramatic increase in global Myc binding and the induction of Myc-dependent gene expression signatures Figs –3, suggeWe identified 1,196 genes that were Myc dependent (pAdj < 0.05) in parental 231 cells. By comparison, there were about 5 times as many Myc-dependent transcripts in 231:TKO cells  Figs  and 6B. We next wondered whether the 1,045 Myc-dependent transcripts common to parental 231 and 231:TKO cells were regulated similarly by Myc. Supporting this notion, the magnitude of Myc dependence of the shared 1,045 genes as a group was not significantly different in the 2 cell populations . FurtherThere were 4,624 transcripts whose expression showed Myc dependence in 231:TKO cells  but not We provide evidence that TXNIP loss leads to an up-regulation of Myc-dependent gene signatures. Our data suggest that TXNIP loss does not regulate Myc’s intrinsic activity as a transcriptional factor per se, but drives Myc-dependent gene expression by dramatically increasing its binding across the genome. TXNIP loss in 2 TNBC cell lines drove the gene expression programs containing known Myc targets. Further, there is a strong negative enrichment for transcripts correlated with TXNIP expression across breast cancers in the METABRIC database and Myc-associated gene signatures. These findings suggest that TXNIP’s ability to regulate Myc’s transcription function is not restricted to TNBC cells lines. Furthermore, TXNIP loss in an immortal, but non-transformed, myoblast cell line also resulted in an increase in Myc-associated gene expression programs. Together, these data suggest that TXNIP may be a general regulator of Myc-dependent transcription, capable of functioning in cells from different lineages and transformation status.Compared to the parental 231 cells, the Myc-dependent transcriptome is expanded in the 231:TKO cells . This fihigh/TXNIPlow gene signature correlates with poor clinical outcomes in TNBCs, but not in other breast cancer subtypes  and 0.1 mM Na2EDTA). Beads were resuspended in 200 ml IP elution buffer (1% SDS and 0.1 M NaHCO3) with vortexing. Beads were incubated in a 65°C bead bath for 1 hour with vortexing the tubes every 15 minutes to elute the antibody-bound chromatin from the beads. Beads were centrifuged at 14,000 rpm for 3 minutes at room temperature. Supernatants (immune-bound chromatin) were collected and transferred to new microcentrifuge tubes. Input samples for each condition served as controls. Immuno-bound chromatin and inputs were de-cross-linked in a 65°C bead bath for overnight.Approximately 20 X 10p-value cutoff of 0.01 and the mfold parameter between 5 and 50. The heatmap was generated using deepTools 2.0 [Reverse cross-linked DNA was purified with ChIP DNA Clean & Concentrator Kit  according to the manufacturer’s protocol. Eluted DNA in EB buffer was used to construct the ChIP library. Preparation of immunoprecipitated DNA for sequencing was performed as previously described . Brieflyools 2.0 . MYC-bouools 2.0 . Myc binools 2.0 ,32 were ools 2.0  was used6 MDA-MB-231 or 231:TKO cells as described above. Myc binding levels on genes were assessed with qPCR. qPCR was performed as described above. ChIP-qPCR primers that were used for experiments: human G0S2, forward:5′-TTCGCGTGCACACTGGCCTTCCC-3′, reverse: 5′-GAGGAGGGGAAAAGGAGGGGGTGGAAC-3′.Anti-Myc immunoprecipitations were performed from chromatin isolated from 20 X 106 cells using the Zymo Research Quick RNA miniprep kit . Approximately 500 ng of total RNA was used to capture mRNA and construct libraries using KAPA Stranded mRNA-Seq Kit  according to the manufacturer’s protocol. Briefly, after mRNA capture and fragmentation, cDNA was synthesized. Sequencing adaptors were ligated to the cDNA fragments. The adaptor-ligated cDNA fragments were amplified with library PCR primers that contain barcodes for about 10 cycles. Libraries were sequenced using either Illumina HiSeq 50 cycles Single-Read Sequencing or Novaseq Paired-Read Sequencing. The resulting Fastq files were aligned to the human genome (hg38) using STAR [p-value less than or equal to 0.05 was used in the DESeq2 program to determine differential gene expression. GSEA and preranked GSEA [Total RNA was extracted from 3 X 10ing STAR . Counts ing STAR  with theing STAR  was usedked GSEA ,32 were ked GSEA  was used2, 10 mM NaCl containing 0.1% NP40, 0.1% Tween-20, and 0.1% Digitonin), and incubated for 3 to 4 minutes on ice. Lysis was quenched with 1 mL of wash buffer (ATAC resuspension buffer containing 0.10% Tween-20); lysed nuclei were counted using Countess II cell counter. Nuclei were pelleted and resuspended in transposition mixture using an in-house prepared Tn5 transposase as described [p-value cutoff of 0.01 and the mfold parameter between 5 and 50. The heatmap was generated using deepTools 2.0 [ATAC-seq was performed on parental MDA-MB-231 and 231:TKO cells with 250,000 cells for each library as described . Brieflyescribed . Sequencescribed  with theescribed . Peaks wescribed  using a ools 2.0 .6 cells per well of a 6-well plate were used. Cells were treated with either 25 nM siNT  or siMyc , 24 hours after plating. Proliferation was monitored for 48 hours after siRNA reagents were added. Proliferation was monitored for 2 days on the Incucyte Zoom Live Cell Imaging Platform (Sartorius) with 10X magnification, and images were captured at 2-hour intervals.A total of 6,000 cells per well were plated in 96-well plates. For the assays with Myc knockdown, 0.5 X 10Cell lines were tested for mycoplasma contamination prior transplantation. Approximately 100,000 of either parental 231 or 231:TKO cells were transplanted into the cleared mammary fat pads of 3- to 5-week-old immunocompromised NOD-scid (NOD.CB17-Prkcd/J) mice as described and under the guidance of the Preclinical Research Resource at HCI . Ten micS1 FigRelated to Fig 1. (A) The relative TXNIP mRNA levels  in parental 231 and 231:TKO cells were determined by RT-qPCR. (B) The expression levels of Myc and TXNIP from approximately 70 breast cancer cells were plotted. Their expression in HCC70 and MDA-MB-231 cells is indicated. (C) Western blotting was used to determine the levels of Myc, TXNIP, and tubulin in 3 biological replicates of parental 231 and 231:TKO cells. (D) Cell proliferation for parental 231 and 231:TKO cells in regular medium over a 48-hour time course was measured based on the percentage of confluency using real-time videography. (E) A volcano plot of the fold changes and adjusted p-values of regulated transcripts in 231:TKO cells. Gene expression changes in 231:TKO cells were determined using DESeq2. (F) A preranked GSEA enrichment plots of the regulated transcripts in 231:TKO cells with the indicated Hallmark datasets. The underlying data for (TIF)Click here for additional data file.S2 FigRelated to Fig 1. (A) Western blotting was used to determine the levels of Myc, TXNIP, and tubulin in 3 biological replicates of parental HCC70 and HCC70:TKO cells. (B) The levels of Myc protein from (A) in parental HCC70 and HCC70:TKO were quantified using ImageJ. (C) Cell proliferation for parental HCC70 and HCC70:TKO cells in regular medium over a 48-hour time course was measured based on the percentage of confluency using real-time videography. (D) Western blotting was used to determine the levels of Myc, TXNIP, and tubulin in parental MB135 and MB135:TKO cells. (E) The levels of Myc protein from (D) in parental MB135 and 135:TKO were quantified using ImageJ. (F) Cell proliferation for parental MB135 and MB135:TKO cells in regular medium over a 48-hour time course was measured based on the percentage of confluency using real-time videography. (G) A preranked GSEA enrichment plot of regulated transcripts in differentiated myoblast MB135:TKO cells with the Hallmark_Myc_Targets_V1 dataset. The underlying data for (TIF)Click here for additional data file.S3 FigRelated to  (A) Transcripts positively correlated TXNIP expression across almost 2,000 breast tumors are negatively correlated with genes in the 4 shown Hallmark datasets or (B) positively correlated with genes in the 4 shown Hallmark datasets.(TIF)Click here for additional data file.S4 FigRelated to  (A) Cell proliferation for 231:TKO+siNT and 231:TKO+siMyc cells in regular medium over a 48-hour time course was measured based on the percentage of confluency using real-time videography. (B) A preranked GSEA was preformed using a ranked list of the differentially expressed genes in 231:TKO+siMyc cells and the indicated Hallmark and Reactome datasets. (C) A ranked list of the 548 reciprocally regulated genes in D) Expression changes of 24 ribosomal protein genes regulated 231:TKO and 231:TKO+siMyc datasets. The underlying data for (TIF)Click here for additional data file.S5 FigRelated to  (A) Genome browser view from RNA sequencing of human G0S2 (G0S2) mRNA in parental 231 and 231:TKO cells. (B) Myc binding, as visualized using IGV_2.5.2, to G0S2 in parental 231 and 231:TKO cells. Putative double E-Box element in the G0S2 promoter [C) Luciferase activities of rat G0S2 reporter in parental and 231:TKO cells with ectopic expression of human TXNIP from pcDNA3 vector or pcDNA3 EV were measured. Luciferase activity was normalized to β-gal activity. At least 2 biological replicates were carried out for all luciferase experiments. Representative figures were shown. Values are reported as mean and standard deviation. **p < 0.01; ***p < 0.001. (D and E) The luciferase activities from WT rat G0S2-luciferase reporter construct and mut rat G0S2-luciferase reporter construct in lysates from parental 231 (D) and 231:TKO (E) were measured. The double E-Box element of G0S2 promoter in the rat G0S2-luciferase construct was deleted using site-directed mutagenesis [p < 0.01; ***p < 0.001. The underlying data for promoter  encompasagenesis . At leas(TIF)Click here for additional data file.S6 FigRelated to  (A) The list of 2,903 genes that showed increased Myc binding in 231:TKO cells compared to parental 231 cells were ranked according to their differential expression in 231:TKO+siMyc cells. This list was analyzed using preranked GSEA to identify enriched pathways in the MSigDB. k/K value is a ratio of number of genes from our dataset (k) divided by the number of genes in the indicated dataset (K). (B) Heatmap of genes regulated in 231:TKO cells that are enriched in the Reactome oxidative phosphorylation dataset. Differential regulation in 231:TKO+siMyc cells are indicated by yellow (up-regulation) or green (down-regulation) boxes. The distances of Myc binding sites from TSS are determined using GREAT [C and D) Differentially down-regulated (C) or up-regulated genes (D) in 231:TKO+siMyc cells were divided into groups based on the number Myc sites associated with each gene. (E and F) The distribution of Myc binding loci relative to the TSS for down-regulated (Myc-activated targets) (E) and up-regulated (Myc-repressed targets) (F) genes in 231:TKO+siMyc cells were annotated using ChIPseeker. The distance to the TSS was then compared change in gene expression following Myc knockdown. The underlying data for ng GREAT . The gen(TIF)Click here for additional data file.S7 FigRelated to Fig 5. (A) The Myc binding sites in our Myc ChIP-sequencing in 231:TKO dataset was compared with Myc binding sites in published Myc ChIP-sequencing datasets GSE77356 and GSE126207 [B) The distance of the 11,145 overlapped Myc binding sites from TSS was annotated using the ChIPseeker program. (C) Myc binding motifs were determined using HOMER. (D) A total of 11,145 overlapped narrow Myc-binding peaks were annotated with genes using GREAT [E) Preranked GSEA using a ranked list of 3,070 Myc-dependent and Myc-bound genes and the Hallmark and Reactome datasets in the MSigDB. k/K value is a ratio of number of genes in our dataset (k) divided by the number of genes in the indicated dataset (K). ggplot2 was used to draw dot plots for pathway enrichment. The underlying data for SE126207 ,42. The SE126207 . The Venng GREAT . A total(TIF)Click here for additional data file.S8 FigRelated to  (A) The fold decrease in Myc mRNA by siMyc in both parental 231 and 231:TKO cells was extracted from our RNA sequencing data. (B) Cell proliferation for parental 231 with siNT or siMyc in regular medium over a 48-hour time course was measured based on the percentage of confluency using real-time videography. (C) The differential expression of genes in 3 different functional groups in parental 231+siMyc and 231:TKO+siMyc datasets were compared. The underlying data for (TIF)Click here for additional data file.S9 FigA and B) To determine the accessibility of chromatin, we used to perform ATAC-seq in both parental 231 and 231:TKO cells. Heatmaps showing the chromatin accessibility in parental 231 and 231:TKO across the entire genome (A) and at Myc-binding sites (B). Heatmaps were generated within 2 kb upstream and downstream of the accessibility peaks using a p-value cutoff of 0.01. (C) Genome browser views of chromatin accessibility in the proximity of RPL10A and SLC18B1 in parental 231 and 231:TKO cells. ATAC-seq, assay for transposase-accessible chromatin using sequencing; RPL10A, ribosomal protein L10a; SLC18B1, solute carrier family 18 member B1; TKO, TXNIP-knockout; TXNIP, thioredoxin interacting protein.((TIF)Click here for additional data file.S10 FigA and B) Western blotting was used to determine the levels of indicated proteins in whole cell lysates (A), cytoplasmic and nuclear fractions (B) from parental 231 and 231:TKO cells. (C) Myc protein was immunoprecipitated with c-Myc antibodies from rabbit (rab) and mouse, respectively. Associated proteins were detected by immunoblotting. (D) Max protein was co-immunoprecipitated with c-Myc antibodies from the cytoplasmic (cyto) and nuclear fractions of parental 231 and 231:TKO cells. The levels of immunoprecipitated Max in these cell lines were assessed by western blotting. (E) Max protein was immunoprecipitated with Max antibody. Associated proteins were detected by immunoblotting. A Mlx IP in was used as a specificity control. The indicated immunoprecipitated proteins were examined by western blotting. (F) Expression levels of the members of the extended Myc family of transcription factors expressed as normalized counts from our RNA-seq analysis. IP, immunoprecipitation; TKO, TXNIP-knockout; TXNIP, thioredoxin interacting protein.((TIF)Click here for additional data file.S1 Data(XLSX)Click here for additional data file.S1 Raw Images(PDF)Click here for additional data file. 1 Aug 2022Dear Dr Ayer, Thank you for submitting your manuscript entitled "TXNIP loss expands Myc-dependent transcriptional programs by increasing Myc genomic binding" for consideration as a Research Article by PLOS Biology. Please accept my sincere apologies for the long delay in getting back to you as we consulted with an academic editor about your submission.Your manuscript has now been evaluated by the PLOS Biology editorial staff, as well as by an academic editor with relevant expertise, and I am writing to let you know that we would like to send your submission out for external peer review.However, before we can send your manuscript to reviewers, we need you to complete your submission by providing the metadata that is required for full assessment. To this end, please login to Editorial Manager where you will find the paper in the 'Submissions Needing Revisions' folder on your homepage. Please click 'Revise Submission' from the Action Links and complete all additional questions in the submission questionnaire.https://www.editorialmanager.com/pbiology) within two working days, i.e. by Aug 03 2022 11:59PM.Once your full submission is complete, your paper will undergo a series of checks in preparation for peer review. After your manuscript has passed the checks it will be sent out for review. To provide the metadata for your submission, please Login to Editorial Manager  corporation #C2354500, based in San Francisco 9 Sep 2022Dear Dr Ayer,Thank you for your patience while your manuscript "TXNIP loss expands Myc-dependent transcriptional programs by increasing Myc genomic binding" was peer-reviewed at PLOS Biology. Please accept my sincere apologies for the delays that you have experienced during the peer review process. Your manuscript has been evaluated by the PLOS Biology editors, an Academic Editor with relevant expertise, and by three independent reviewers.The reviews are attached below. You will see that the reviewers find your manuscript interesting and well done, but raise overlapping concerns with the overall strength of the mechanistic insights into how TXNIP regulates Myc transcriptional activity. In addition, they note that the physiological and biological significance of the findings should be strengthened, by including data from several cell lines and using in vivo mouse models to demonstrate a role for TXNIP in tumorigenesis.Based on the reviews and following discussion with the academic editor, I regret that we cannot accept the current version of the manuscript for publication. We remain interested in your study and would be willing to consider resubmission of a comprehensively revised version that thoroughly addresses all the reviewers' and Academic Editor’s comments. 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Please don't hesitate to contact us if you have any questions or comments.Sincerely,RichardRichard Hodge, PhDAssociate Editor, PLOS Biologyrhodge@plos.org-----------------------------------------REVIEWS:Reviewer #1: In this paper, Lim et al have examined the consequences of TXNIP gene knockout in the MDA-MB231 TNBC cell line. They found nearly 1800 differentially expressed transcripts to be altered in response to this loss. Interestingly, among the most highly and selectively enriched gene sets were those which are known direct Myc targets. The change in Myc target expression in response to RXNIP inactivation is both quantitative and qualitative; previously bound target genes increase their Myc binding by an average of two-fold and genes that did not bind Myc previously in control cells now bind Myc in TXNIP KO cells. The other top gene sets encoded proteins involved in mitochondrial structure and function, translation and cell cycle. It is known that many of the genes within these sets are also direct Myc target. Overall, these findings indicate TXNIP to be a generalize repressor of Myc target gene regulation.MAJOR POINTS:1. The authors should state precisely how many known Myc targets are enriched (both positively and negatively) 2. The gene sets described in Fig. 1B other than "Myc Target Genes" represent many functions that nonetheless have been described as being Myc-regulated . How many of the genes within these sets are known to be direct Myc targets? Knowing this would allow the authors to increase the number of genes that they state are Myc targets but are not listed as such simply because they are classified as being members of another category. Another way to address the point above is to subtract from the 1800 differentially expressed 231-TKO genes those that are identified as Myc targets and then ask whether the remainder have ever been identified as being direct Myc targets in any other cell lines by searching the ENCODE data base. The Myc target genes identified by the authors represents only a tissue-specific snapshot of potential targets. Doing a broader survey of cell lines other than MB231 might be a more sensitive and comprehensive way of identifying those TXNIP targets that are either definite direct Myc targets or have the potential to be as a result of TXNIP KO. 3. The authors should more thoroughly discuss the fact that the numbers of both positive and negative Myc targets seem to increase in response to TXNIP inactivation. The former are those whose activity is due to Myc's binding directly to the 5'ends of genes via either E boxes or ChoREs (well discussed in the ms.) whereas the latter suppress transcription, most likely indirectly by binding to and interfering with transcription factors such as Miz1 and Sp1 that bind to inR elements and Sp1 sites, respectively (not as well-discussed). Given that both types of interactions seem to be affected by TXNIP KO, it would seem logical to attribute this to some fundamental change in either Myc or Max. The most obvious type of change would be one that affected Myc-Max heterodimerization or binding to E-boxes/ChoRES and to Miz1/Sp1. This could happen if the fraction of Myc that associated with Max was increased, either via more efficie Myc-Max association or by decreasing the abundance of one of the Mxd members that competes with Myc for Max occupancy. The former state might be the result of some type of post-translational modification of Myc and/or Max that increased their ability to heterodimerize or bind DNA afterwards. This could be due to an altered intracellular redox state, which seems highly likely given that TXNIP plays a major role in maintaining redox balance via its inhibitory effect on thioredoxin. Although the authors' observation is a fascinating one, it lacks any mechanistic insight into how this is occurring. At the very least, the authors should investigate the relative abundance of Myc-Max and relevant Mxd-Max heterodimers. Reduced levels of one or more Mxd members might also drive a greater amount of Myc-Max heterodimer formation simply via mass action. As to determining the underlying basis by which Myc family heterodimer levels might be altered, the authors should consider investigating the redox state of their MDA-MB231 control and TXNIP KO cells. A very straight forward and easy way to do this would be to employ roGFP, which can be targeted to either the cytoplasm or mitochondria :13044-53). MINOR POINTS: Fig. 1E shows a FDR q value of <0 which doesn't make sense. The actual p value should be indicated. In addition, for C and D, both P values are >0.05. The authors should state in the figure legend the criteria used that allow them to justify representing these q values as indicating significant enrichment. Fig. 3. Are the 3 clusters distinguished in anything other than the distance their Myc binding sites are from the TSS of their respective genes and the affinity of these sites for Myc? From these data, is it fair to say that, as a rule of thumb, low-affinity Myc binding sites tend to be located progressively further away from the TSS?Fig. 3F & line 270. The authors should explain to the more general reader what the k/K ratio represents.Line 330-332. The authors refer to a ChORE element in the rat GOS2 gene that is just upstream of the TSS and that is presumably the functional equivalent of the somewhat degenerative element they identified in the human GOS2 gene's promoter (lines 307-308). How related/conserved are these two elements? Line 377: The title of this section is: "TXNIP Controls Myc Transcriptional Programs by increasing Myc Binding". This should be changed given that it is the LOSS of TXNIP that increases Myc binding (lines 396-397: "These results suggest that TXNIP loss increases Myc-dependent gene expression by increasing Myc genome occupancy.") Reviewer #2: In "TXNIP loss expands Myc-dependent transcriptional programs by increasing Myc genomic binding", Lim and colleagues explore the role of TXNIP in negatively regulating MYC DNA binding in triple-negative breast cancer. The Authors begin by showing in a TNBC line that knockdown of TXNIP leads to upregulation of transcriptional programs associated with MYC, and this pattern is recapitulated in human breast cancer samples and an unrelated muscle cell line. siRNA-mediated knockdown of MYC in the background of TXNIP loss further solidifies this association. The Authors next used ChIP-sequencing to look at how MYC DNA binding changes in the absence of TXNIP. Interesting, they show three clusters of MYC binding; the strongest cluster bound to classic MYC proximal promoter sites, while the weakest cluster bound to more distal and less class MYC sites. Finally, the Authors knock down MYC in a TXNIP-competent cell line and show that while the number of MYC sites in the presence or absence of TXNIP varies, the average degree to which MYC upregulates its targets does not vary. Overall, this suggests that TXNIP, through a still-unknown mechanism, impacts MYC genomic binding availability but not MYC activity. This manuscript generally accomplishes what it sets out to determine, which is the role of TXNIP in restraining MYC genomic binding and activity in TNBC. The Authors successfully backed up their RNA-seq and ChIP-seq data with specific examples throughout the paper, and the finding in Figure 6 that enhanced MYC DNA binding does not necessarily lead to higher levels of gene expression is particularly interesting and important. There are a few issues that will need to be addressed, detailed in the list below. Most important of these are comparing different knockdown efficiencies of MYC in their two MDA-MB-231 lines, including proliferation assays for other manipulations besides TXNIP knockdown, and potentially expanding on the mechanistic role of TXNIP in controlling MYC activity, which is hinted at in the Discussion but without data. Major  points:* The comparison between 231:TKO siMYC and 231 parental siMYC is complicated by different knockdown efficiencies of MYC. The contrasting on the western blots makes it difficult to determine the degree of knockdown, but comparing the qPCRs in S3B and S6A, it appears that the knockdown is at least ~3X efficient in the TKO than in the parental cells. This affects interpretation of Figure 6, as less MYC knockdown in parental siMYC cells might naturally lead to less lost MYC-regulated genes. I understand that CRISPR knockout of MYC is likely impossible in these (and most) cells, and that siRNA is not easily tuned to a specific degree of knockdown, but the Authors should support their findings in Figure 6 with an additional method of MYC inhibition, such as expression of OmoMyc or use of a MYC-targeting pharmacologic agent such as MYCMI. A repeat of the RNA-seq experiment is not necessary; instead, repeating some of the individual genes in 6D would be sufficient.* The mechanism of how TXNIP regulates MYC remains unclear. In the Discussion, the Authors state that, "Our preliminary experiments provisionally rule out a role for TXNIP in regulating global chromatin accessibility, the amount of Myc in the nucleus, the formation of Myc:Max heterodimers, or Myc's association with cofactors required for genome binding such as WDR5 (46); unpublished data)." Any of these results would be highly welcomed as negative results in the Supplemental Data section, particularly those connected to global chromatin accessibility. In particular, a change in chromatin accessibility upon TXNIP loss would be fully consistent with the idea of MYC as a global amplifier of transcription, while a lack of correlation between TXNIP loss and major changes in chromatin accessibility would be an interesting counterpoint to this model. If the Authors are not ready to show these data or other data mentioned in the Discussion in the paper, they should remove this sentence.* I believe that Figure 6C is the most important panel in the entire paper, as it shows that the degree of expression regulation by MYC is not changed in the 231:TKO siMYC versus 231 parental siMYC despite the different numbers of MYC targets. However, this panel is somewhat difficult to read and interpret. In addition to 6C itself, it would be useful for the Authors to show these data another way, such as overlapping histograms showing degree of expression in the two models.* For the same reason that it was important to include a proliferation assay for 231:TKO cells , the Authors must include proliferation assays for other manipulations, such as the 231:TKO + siMYC cells and the parental 231 siMYC cells. This will help with evaluation of some of the RNA-sequencing results, particularly those related to cell cycle pathways, which may be regulated by MYC but also by proliferation state in general. A difference in growth between the 231:TKO + siMYC cells and the parental 231 siMYC might even suggest that the parental 231 siMYC are less able to tolerate MYC knockdown (see comment below about different degrees of siRNA efficiency). * There are several pieces of data in the paper that are lacking in an explanation of the Methods, these need to be included:1) How TXNIP mRNA was used to rank the levels of all other genes in 1904 breast cancer lines, and to create a single pre-ranked list for GSEA analysis.2) How GSEA results throughout the paper were identified for presentation. Were these based on rankings of NES strength, or hand-curated from a larger list of results? I am not opposed to the results being hand-curated since the Authors are focused on pathways related to MYC and metabolism, but this must be clearly stated.Minor  points:* The Authors should discuss why MDA-MB-231 was chosen, particularly with regard to MYC status. Is MYC amplified in these cells? If not, is it highly expressed compared to other TBNC lines or other breast cancer lines? A supplemental graph using data from the Cancer Cell Line Encyclopedia / DepMap to show where MDA-MB-231 MYC expression falls in breast cancer cells lines would be useful. This information is important in evaluating the conclusions of the paper. Since not all cancers have elevated MYC, TXNIP deletion in cancers with closer to wild-type levels of MYC may perhaps not result in expanded MYC DNA binding, due to lack of excess MYC protein.* In Figure 6, comparing 231:TKO siMYC and 231 parental siMYC, are there pathways that are enriched in 231:TKO siMYC but not in the parental? It might be useful to include a panel that outlines a few of these pathways, along with focusing on the change in enrichment in existing pathways in Figure 6E* The western blot in Figure S1E should be rerun so that the parental and TKO are on the same blot, and can be uniformly contrasted.Reviewer #3: The MYC protooncogene plays a important role in the regulation of metabolism including there regulation of glucose uptake to drive glucose dependent biosynthetic pathways. MYC regulates these processes through transcriptional regulation of genes including those that drive the expression of glucose transporters. Further, the authors previously have shown that MYC represses the expression of Thioredoxin Interacting Protein (TXNIP). This serves as a potent negative regulator of glucose uptake. They showed before that a Myc high /TXNIP low gene signature may be clinically significant because it appears to predict the overall clinical prognosis in Triple-Negative Breast Cancer (TNBC) but not in other subtypes of breast cancer. Now the authors have examined further the role of TXNIP function and how it may contribute to the aggressive behavior of TNBC. They generated TXNIP null MDA-MB-231 (231:TKO) cells. They found that TXNIP loss drives a transcriptional program that resembles those driven by Myc. They suggest that this happens because it increases global Myc genome occupancy. Thereby, they conclude that TXNIP loss allows Myc to invade the promoters and enhancers of target genes that are potentially relevant to cell transformation. They suggest that TXNIP is a broad repressor of Myc genomic binding. The increase in Myc genomic binding in the 231:TKO cells expands the Myc-dependent transcriptome. They argue that this leads to the expansion of Myc- dependent transcription following TXNIP loss occurs without an apparent increase in Myc's intrinsic capacity to activate transcription and without increasing Myc levels. Hence they suggest that TXNIP loss mimics Myc overexpression, connecting Myc genomic binding and transcriptional programs to the metabolic signals that control TXNIP expression.Overall these results are potentially interesting but preliminary and provide only limited additional information compared to the authors previously published work. There is essentially data from only one cell line, in vitro, without a specific mechanism, or demonstration that the is a causal role in tumorigenesis or even in change in metabolism. There is only limited effort to validate that other potential mechanisms have been considered.First, the experiments are essentially performed in one immortal human tumor derived cell line. Although the observations are compared to previously archived data, the main experiment is a single KO in a single cell line. This is a reasonable start, but to say that the results generally apply, or are specific to TNBC, is not justified based upon this data.Second, the results are only performed using in vitro data. And, there is no experimentation to see if any of the effects on gene expression or effects of the KO have any effects on actual tumor biology, invasive behaviorr, dependence or changes in metabolism.Some validation of observations using mouse models, xenografts, and/or other human-tumor derived cell lines should be included.Third, the notion that MYC transcriptional effects are contextually dependent upon other gene products, metabolism, and/or transcriptional mechanisms has been well established by a multitude of investigators. The role of TXNIP and why this is novel beyond the authors prior work is not clear. Hence, the novelty and significance of the results needs to be clarified.Fourth, the presumption that there are no effects on MYC expression are based upon limited data, such as a single Western blot that is not quantified. Seems very unlikely that there are no effects on MYC mRNA, protein expression stability. The constitutive KO is likely to have other effects on the cell line. Fifth, the mechanism proposed, that MYC promoter binding is globally enhanced as if MYC is overexpressed needs to be clarified. What is the mechanism? Do the authors think actually that a single gene KO always has the effect on MYC? Or only in this cell line? Or only in TNBC? is this a direct mechanism? How? How does this relate to the Levens and Young transcriptional enhancer model? Does this only explain "high" MYC then what is "high" versus physiologic? Overall, the authors make an interesting observation suggesting that KO of TXNIP influencing MYC transcription in one tumor cell line, but the results at this juncture are preliminary. 20 Jan 2023AttachmentPBIOLOGY-D-22-01559R2_RESPONSE_1-20-2023.docxSubmitted filename: Click here for additional data file. 2 Feb 2023Dear Dr Ayer,Thank you very much for your patience while we considered your revised manuscript "TXNIP loss expands Myc-dependent transcriptional programs by increasing Myc genomic binding" for publication as a Research Article at PLOS Biology. 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Drosophila male germline proceeds through a unique transcriptional program controlled both by germline-specific transcription factors and by testis-specific versions of core transcriptional machinery. This program includes the activation of genes on the heterochromatic Y chromosome, and reduced transcription from the X chromosome, but how expression from these sex chromosomes is regulated has not been defined. To resolve this, we profiled active chromatin features in the testes from wildtype and meiotic arrest mutants and integrate this with single-cell gene expression data from the Fly Cell Atlas. These data assign the timing of promoter activation for genes with germline-enriched expression throughout spermatogenesis, and general alterations of promoter regulation in germline cells. By profiling both active RNA polymerase II and histone modifications in isolated spermatocytes, we detail widespread patterns associated with regulation of the sex chromosomes. Our results demonstrate that the X chromosome is not enriched for silencing histone modifications, implying that sex chromosome inactivation does not occur in the Drosophila male germline. Instead, a lack of dosage compensation in spermatocytes accounts for the reduced expression from this chromosome. Finally, profiling uncovers dramatic ubiquitinylation of histone H2A and lysine-16 acetylation of histone H4 across the Y chromosome in spermatocytes that may contribute to the activation of this heterochromatic chromosome.Spermatogenesis in the  Drosophila male germline that are used to activate and regulate gene promoters during sperm development  mutant males arrests in the spermatogonial stage, so their testes are full of early germline cells  mutants arrests in the early primary spermatocyte stage, thus enriching for this cell type . To aid distinguishing germline from somatic cell-type chromatin features, we also profiled wing imaginal discs from larvae. Sequencing from replicates was pooled, providing 4.4–19.2M reads/genotype, and publicly available coverage tracks are posted here.To profile chromatin features of gene activity during spermatogenesis, we performed CUT&Tag profiling for histone H3 lysine-4 dimethylation (H3K4me2), which marks active promoters and enhancers . The adune cells . The gerell type . Betweennanos (nos) is marked with the H3K4me2 modification in bam testes, with less signal in aly or in wildtype testes , and zero population growth (zpg) are each heavily marked with H3K4me2 in bam mutant samples, reflecting their activity  which are primarily expressed in late spermatocytes  and cookie monster (comr) gene promoters which produce mRNA in mid-stage spermatocytes, but are most heavily marked with the H3K4me2 modification in wildtype testes. Second, some promoters acquire the H3K4me2 modification well before mRNA accumulates. A small number of genes are expressed in the post-meiotic stages of spermatogenesis, including the ‘cup’ genes (ryder cup (r-cup) is already marked in aly mutant testes, implying that it is already active in pre-meiotic stages  gene encodes an RNA-binding protein that is broadly expressed, but in spermatocytes Heph binds the abundant nuclear transcripts from the Y chromosome fertility genes  and GFP signal of each event  of the C-terminal tail of the largest subunit of the complex. Inspection of genome landscapes demonstrates the high quality of these profiles. For example, the meiotic beta-tubulin variant gene ic cells .heineken-cup (h-cup), implying that RNAPII is engaged at some genes well before their transcripts are detected.Elongating RNAPII is also detectable at many genes that accumulate transcripts in late spermatocytes. For example, 14 genes encoding protamines that package the genome in sperm  are heavbetaTub85D differs from the typical pattern across active genes in somatic cells. Serine-2-phosphorylation of RNAPII is associated with transcriptional elongation, but in Drosophila and in mammalian somatic cells it shows a prominent peak at the 5’ end of active genes  gene, which is almost 5 kb and is highly expressed. Strikingly, RNAPIIS2p signal at stc shows a prominent peak near the promoter in somatic wing imaginal disc cells but is broadly distributed across the gene in spermatocytes , and increases RNAPII density  is generally associated with heterochromatic silencing and marks the precociously silenced X chromosome in male mouse spermatogenesis ) in spermatocytes (A major system of chromatin repression uses trimethylation of histone H3 at lysine-27 (H3K27me3) to direct developmental gene silencing . Althougatocytes . There iatocytes .X chromosome in male mammals is the mono-ubiquitinylation of histone H2A at lysine-119 (uH2A)  . This mokaryotes . We theratocytes . Thus, tomosomes .Y-linked genes as they are expressed . The 1118w strain was used as a wildtype control. The heph-GFP males used for profiling have the genotype CC00664/TM3, Ser Sby w/Y; P[PTT-GC]heph. The bam mutant males have the genotype D86/Df(3R)FDD-0089346w/Y; e bam. The aly mutant males have the genotype 1 ry506 e/Df(3L)BSC428P[ry11]ry2, mwh aly. Additional genotypes used for cytological characterization were +]1/Y; P2/2; P[PTT-GC]hephCC00664/3y w P3w.All crosses were performed at 25°C. All mutations and chromosomal rearrangements used here are described in Flybase  for 10 min, stained with 0.5 μg/mL DAPI/PBS, and mounted in 80% glycerol on slides. Testes were imaged by epifluorescence on an EVOS FL Auto 2 inverted microscope (Thermo Fisher Scientific) with a 10× objective.Testes from third-instar male larvae were prepared as described . Briefly2 for 1 hr at 37°C to tagment chromatin. Tissues were then dissociated with collagenase  in HEPESCA  solution at 37°C for 1 hr. We then added SDS to 0.16%, protease K to 0.3 mg/mL, and EDTA to 16 mM and incubated at 58°C for 1 hr, and DNA was purified by phenol:chloroform extraction and ethanol precipitation. Libraries were prepared as described (To perform CUT&Tag for whole tissues (‘whole-mount CUT&Tag’), we dissected 10 testes from 1-day-old adults or 10 imaginal wing discs from third instar larvae in PBS buffer supplemented with cOmplete Protease Inhibitor (Roche 11697498001). Dissected tissues were permeabilized with 0.1% Triton/PBS for 30 min at room temperature, and then manually transferred into the following CUT&Tag solutions sequentially between wells of a glass dissection plate: primary antibody solution  overnight at 4°C, secondary antibody solution (in Wash+ buffer) for 1 hr at room temperature, and then incubated with loaded protein-A-Tn5 ] for 1 hr. After one wash with 300Wash+ buffer, samples were incubated in 300Wash+ buffer supplemented with 10 mM MgClescribed , with 14heph-GFP males and digested in 200 µL of 2 mg/mL collagenase (Sigma C9407) in HEPESCA solution at 37°C for 1 hr. The sample was then repeatedly pipetted with a P200 pipette tip to dissociate the tissue, then passed through a 35 µM filter with 5 mL collection tube (Corning 352235) on ice. The filter was washed with PBS to bring the total volume of collected filtrate to 1 mL. A Sony MA900 Multi-Application Cell Sorter with a 100 µM nozzle, flow pressure of 2, GFP laser settings of 32%, and FSC = 1 was used for isolating cells. Isolated cells were collected in 1 mL of PBS in 5 mL tubes. Benchtop CUT&Tag was performed on these samples as described  and with consensus sequences for 128 transposon sequences (https://github.com/bergmanlab/drosophila-transposons/blob/master/misc/D_mel_transposon_sequence_set.fa) appended (--end-to-end --very-sensitive --no-mixed --no-discordant -q --phred33 -I 10 -X 700).To streamline analysis of repetitive transposons in the fly genome, we used a modified version of the release r6.30 appended . Paired-https://genome.ucsc.edu/s/jamesanderson12358/analysis230508___UCSC_session_germline_MS) for visualization, and selected regions were exported as PDF files.Mapped reads from whole-tissue replicates were merged using samtools-merge and converted to coverage tracks using bedtools-genomecov with options -scale -fs. For profiling FACS-isolated spermatocytes, duplicate reads were removed from each library using Picard-remove duplicates, and then replicates were merged using samtools-merge and converted to coverage tracks using bedtools-genomecov with options -scale -fs. These tracks are hosted at UCSC , and matched FCA expression data for 40 testis cell types  and its average expression in 21 somatic groups (sexp). The 40th ‘unannotated’ group was not considered for gexp or sexp values. We then used k-means clustering (k=10) to group genes by cell-type expression within the testis . The k-m2fold-change≥1 average expression in germline groups than in testis somatic groups (termed genes with germline-enriched expression). This table is included as We then selected 6419 genes with logFor each gene, we determined the identity and distance to the nearest promoter of the next upstream gene using the bedtools/closest with parameters: -D a -fu, and for the next downstream gene with parameters: -D a -fd.bam, aly, and wildtype testis samples, and these values are appended to To summarize the enrichment of chromatin marks at promoters, we counted mapped reads in an interval from –200 to +500 bp around each TSS in merged profiling data by summing reads using deeptools/multiBamSummary with parameters: BED-file –BED and scaled counts by the number of reads in each library /(number of reads in library) to give counts per million. Profiling counts were transformed into z-scores for each promoter between To summarize the enrichment of chromatin marks across genes, we counted mapped reads from the start to the end of each gene in merged profiling data by summing reads using deeptools/multiBamSummary with parameters: BED-file –BED and scaled counts by the number of reads in each library and the length of the gene /(number of reads in library * gene length in kb) to give counts per kilobase per million (CPKM), and these values are appended to To summarize enrichment of chromatin marks across transposons, we counted mapped reads across consensus transposon sequences using deeptools/multiBamSummary with parameters: BED-file –BED and scaled counts as CPKM. These values are provided in For average plots of H3K4me2 signal around promoters, profiling coverage was summarized with deepTools/bamCoverage ± 1 kb around annotated TSSs excluding regions with a second gene promoter in the display window with 10 bp binning, and plotted using plotHeatmap.For average plots of H3K4me2 signal around promoters, profiling coverage was summarized with deepTools/bamCoverage ± 1 kb around annotated TSSs excluding regions with a second gene promoter in the display window with 10 bp binning, and plotted using plotHeatmap.For heatmapping of RNAPIIS2p signal at gene starts, we used deepTools/computeMatrix with parameters: -b 2000 -a 2000 -R and then we used deepTools/plotHeatmap with parameters: --colorMap viridis.For visualizing the chromosomal distribution of CUT&Tag data as CIRCOS plots, we used the circlize package in R with default settings (circlize version 0.4.15). Genome coverage files for plotting were generated by deepTools/bamCoverage command, using parameters:-bs 20000 --centerReads --effectiveGenomeSize 142573017 -of bedgraphAnd plotted in consecutive 20 kb bins. The innermost three rings of each plot display genomic coverage, with color-coding set independently per ring. The color of bins in the outer ring correspond to the fold-change of signal in spermatocytes compared to wing imaginal discs calculated using deepTools/multiBigwigSummary command, with parameters:bins -bs 20000 –outRawCounts2 & 3’ category and plotted, discarding genes with enrichment score = 0 in either dissociated testes, in spermatocytes, or in wing imaginal discs.For boxplots, the enrichment score for each gene was scaled by dividing its read count by the median count in the ‘chromosome  Drosophila and transcriptional profiling in single cells/nuclei. This description of the dramatic changes in chromatin structure during spermatogenesis leads to some new observations, with convincing evidence, and it is useful for the field.Using a variety of methods including mutant analyses, the authors study chromatin structure during spermatogenesis in  Drosophila spermatogenesis. Their main approaches include (1) Using two different genetic mutants that arrest male germ cell differentiation at distinct stages, bam and aly mutant, they performed CUT&TAG using H3K4me2, a histone modification for active promoters and enhancers; (2) Using FACS sorted pure spermatocytes, they performed CUT&TAG using antibodies against RNA PolII phosphorylated Ser 2, H4K16ac, H3K9me2, H3K27me3, and ubH2AK118. They also compare these chromatin profiling results with the published single-cell and single-nucleus RNA-seq data. Their analyses are across the genome but the major conclusions are about the chromatin features of the sex chromosomes. For example, the X chromosome is lack of dosage compensation as well as inactivation in spermatocytes, while Y chromosome is activated but enriched with ubH2A in spermatocytes. Overall, this work provides high quality epigenome data in testes and in purified germ cells. The analyses are very informative to understand and appreciate the dramatic chromatin structure change during spermatogenesis in Drosophila.Anderson, Henikoff and Ahmad et al. performed a series of genomics assays to study  Drosophila. The experiments and analyses were well done, by a combination of the latest and appropriate methods. They include appropriate numbers of replicates. Results were parsed by comparing them among wildtype and two mutant with different arrest stages in spermatogenesis, as well as in FACS-sorted spermatocytes. The authors profiled larval wing discs as reference-somatic cells, allowing focus on features associated with germ cells; comparisons to testis somatic cells provided further specificity. Results were further refined by categorizing genes of interest based on available single nucleus RNA seq expression profiles. The authors acknowledge that the paper's interpretations are based on subtractive logic using the mutants, but comment that more precise ways of staging would not have yielded sufficient sample for their methods.Anderson et al profiled chromatin features, including active chromatin marks, RNA polymerase II distribution, and histone modifications in the sex chromosomes of spermatogenic cells in Drosophila spermatocytes.The authors documented differences in the distribution of RNAPIIS2p on some genes in germ cells vs somatic cells, the presence of a uH2A body beginning in early spermatocytes, and high levels of uH2A on the Y chromosome with little or none on the X, which is intriguing because uH2A is usually associated with silencing, yet the Y chromosome is active in spermatogenic cells. All of these are new, interesting, and important. Also importantly, the authors' data provide molecular details consistent with lack of MSCI, and lack of dosage compensation of the X chromosome in  The following is the authors’ response to the original reviews.Public Reviews:Reviewer #1 (Public Review):Drosophila spermatogenesis. Their main approaches include (1) Using two different genetic mutants that arrest male germ cell differentiation at distinct stages, bam and aly mutant, they performed CUT&TAG using H3K4me2, a histone modification for active promoters and enhancers; (2) Using FACS sorted pure spermatocytes, they performed CUT&TAG using antibodies against RNA PolII phosphorylated Ser 2, H4K16ac, H3K9me2, H3K27me3, and ubH2AK118. They also compare these chromatin profiling results with the published single-cell and single-nucleus RNA-seq data. Their analyses are across the genome but the major conclusions are about the chromatin features of the sex chromosomes. For example, the X chromosome is lack of dosage compensation as well as inactivation in spermatocytes, while Y chromosome is activated but enriched with ubH2A in spermatocytes. Overall, this work provides high-quality epigenome data in testes and in purified germ cells. The analyses are very informative to understand and appreciate the dramatic chromatin structure change during spermatogenesis in Drosophila. Some new analyses and a few new experiments are suggested here, which hopefully further take advantage of these data sets and make some results more conclusive.Anderson, Henikoff, Ahmad et al. performed a series of genomics assays to study Major comments:1. The step-wise accumulation of H3K4me2 in bam, aly and wt testes are interesting. Is it possible to analyse the cis-acting sequences of different groups of genes with distinct H3K4me2 features, in order to examine whether there is any shared motif(s), suggesting common trans-factors that potentially set up the chromatin state for activating gene expression in a sequential manner?While the histone H3K4me2 mark is low and more widespread at genes active in late spermatocytes and in spermatids , we suggest that this may be due to a general decrease in the importance of this modification in late spermatogenesis rather than a specific feature of those genes. We point this out in lines 146-152. This idea is supported by the widespread change in RNAPII distribution in all genes in the germline, shown in Figure 3F and supplementary Figure 2.1. Pg. 4, line 141-142: "we cannot measure H3K4me2 modification at the bam promoter in bam mutant testes or at the aly promoter in aly mutant testes", what are the allelic features of the bam mutant and aly mutant? Are the molecular features of these mutations preventing the detection of H3K4me2 at the endogenous genes' promoters? Also, the references cited  and  are not the original research papers where these two mutants were characterized.Drosophila oogenesis. Development 118(3): 797--812.). The aly1 allele is also a P element-induced mutation; it is not molecularly characterized . Coordinate developmental control of the meiotic cell cycle and spermatid differentiation in Drosophila males. Development 122(4): 1331--1341.) We noticed a lack of reads for various histone modifications in aly mutants in part of the gene, suggesting that the deletion is limited to the promoter and the first exon. Signal for the H3K4me2 modification is at background levels for the distal portion of aly, suggesting that the deletion inactivates the gene.We have corrected these citations to the original papers. We clarified in the text that the bamΔ86 allele is a deletion of almost all of the coding sequence . Expression of the Sex-lethal gene is controlled at multiple levels during 1. The original paper that reported the Pc-GFP line and its localization is: Chromosoma 108, 83 (1999).We now cite the first published description of this marker in the male germline and a more detailed one (lines 291-293).The Pc-GFP is ubiquitously expressed and almost present in all cell types. In Figure 6B, there is no Pc-GFP signals in bam and aly mutant cells.We apologize, our labeling of the figure was easily overlooked - the bam and aly genotypes do not carry the PcGFP marker, since we didn’t need it for staging the germline nuclei. We have clarified this in the figure.According to the Method "one testis was dissected", does it mean that only one testis was prepared for immunostaining and imaging? If so, definitely more samples should be used for a more confident conclusion.We corrected the text to make it clear that all cytological examinations were repeated at least 10 times (lines 438-439).Also, why use 3rd instar larval testes instead of adult testes?Generally, we find that immunostaining of the larval testes is cleaner, and we now mention this in the Methods (lines 439-440). We have immunostained both larval and adult testes for these markers with consistent results.Finally, it is better to compare fixed tissue and live tissue, as the Pc-GFP signal could be lost during fixation and washing steps. Please refer to the above paper  for Pc-GFP in spermatogonial cells and Development 138, 2441-2450 (2011) for Pc-GFP localization in aly mutant.We are using PcGFP staining for staging with antibody detection of other chromatin features, which requires fixed material, although we have compared PcGFP signal in both live and fixed tissue. We have added the 1999 reference for nuclear staging in the male germline.1. Ubiquitinylation of histone H2A is typically associated with gene silencing, here it has been hypothesized that ubH2A contributes to the activation of Y chromosome. This conclusion is strenuous, as it entirely depends on correlative results.We agree that this is a correlation. We cite in the text examples where uH2A is associated with gene activation. We have added a comment to clarify that this is a correlation (lines 318-320), and now present an alternative that uH2A on the Y chromosome may be moderating expression from these highly active genes (lines 405-407).For example, the lack of co-localization of ubH2A immunostaining and Pc-GFP are not convincing evidence that ubH2A is not resulting from PRC1 dRing activity. It would be a lot stronger conclusion by using genetic tools to show this. For example, if dRing is knocked down  or mutated in spermatocytes , would they detect changes of ubH2A levels?Drosophila genome and that in other species RING1 is not responsible for sex body uH2A in the male germline (lines 394-396).We have tested multiple constructs to knockdown dRING using the bam-GAL4 driver although we have not reported it in the manuscript. These knockdowns have no effect on uH2A staining in the testis, on motile sperm production, or on male fertility, although these RNAi constructs do produce Polycomb phenotypes when expressed in somatic cells from an en-GAL4 driver. This is the reason why we point out in the text that there are multiple alternative candidates for an H2A ubiquitin ligase in the 1. Regarding "X chromosome of males is thought to be upregulated in early germline cells", it has been shown that male-biased genes are deprived on the X chromosome , so are the differentiation genes of spermatogenesis [Cell Research 20:763-783 (2010)]. It would be informative to discuss the X chromatin features identified in this work with these previous findings.Drosophila X chromosome is moderately depleted of male germline-expressed genes (lines 362-363).We now mention that the For example, the lack of RNAPII on X chromosome in spermatocytes could be due to a few differentiation genes expressed in spermatocytes located on the X chromosome.We show in Figure 3B that there is a minor non-significant reduction in RNAPII on the X chromosome in spermatocytes. This small reduction might be due to the moderate paucity of male germline-expressed genes on this chromosome, but since it is non-significant we have not discussed it.Reviewer #2 (Public Review):Drosophila. The results are new and the experiments and analyses look well done, including with appropriate numbers of replicates. Results were parsed by comparing them among two arrest mutants and wildtype, as well as in FACS-sorted spermatocytes. The authors also profiled larval wing discs to serve as reference-somatic cells, which allowed them to focus only on features in their testis data that were associated with germ cells. Their results were further refined by categorizing the genes of interest based on available single nucleus RNA seq expression profiles. The authors document interesting phenomena, such as differences in the distribution of RNAPIIS2p on some genes in germ cells vs somatic cells, the presence of a uH2A body beginning in early spermatocytes, and high levels of uH2A on the Y chromosome and little or none on the X. The former is intriguing because this modification is usually associated with silencing, yet the Y chromosome is active in spermatogenic cells. The authors interpret some of their data as implying a lack of dosage compensation of the X chromosome in spermatocytes.Anderson et al profiled chromatin features, including active chromatin marks, RNA polymerase II distribution, and histone modifications in the sex chromosomes of spermatogenic cells in https://doi.org/10.1126/science.aal3096, https://doi.org/10.1101/gad.335331.119), but they should be aware of them and of their results.The data are believable and new, but it is not fully clear how to interpret them. The paper's interpretations rely on subtractive logic to parse results from mixtures of cells down to cell type, extracting spermatogonia, spermatocyte, etc. features by comparing bam mutants (only spermatogonia) to aly mutants (spermatogonia and early spermatocytes but no later stages) to wildtype , and extracting testis germline data by comparison to wing disc soma; their FACS sorted spermatocytes also have heterogeneity. I recognize that the present paper was a lot of work and am not suggesting that the authors redo their study using methods that give more purity and precision of stage .The conclusions about dosage compensation are indirect, but are consistent with the current model documented in the studies cited by the authors, as well as earlier studies (doi: 10.1186/jbiol30).We disagree; our data directly speaks to the molecular mechanisms at play. Our profiling of the H4K16 acetylation mark and RNAPII in isolated spermatocytes  demonstrates that current models are correct, and so are useful for settling this point in the literature.Reviewer #1 (Recommendations For The Authors):Throughout the manuscript, it is better to cite the original research papers.We have added citations for the original characterizations of bam and aly alleles used, for the descriptions of PCGFP in spermatocytes, and for issues raised by reviewer comments.Minor comments:Pg.2, line 70-71: "Germline stem cells at the apical tip of the testis asymmetrically divide to birth spermatogonia", should be gonialblast.Fixed (line 71).Pg.2, line 71: "four rapid mitotic divisions", the spermatogonial cell cycle lasts several hours-- "rapid" is subjective and relative, better to leave this word out.Fixed (line 71).Reviewer #2 (Recommendations For The Authors):Other than the major issue raised in the public review this paper only needs a few minor modifications, listed by line number below. The first one would be considered essential by this reviewer.Drosophila.27: In the sentence that ends on this line, please add the word testis after Fixed (line 27).119: It must be known from the Fly Cell Atlas data whether these genes do begin to express in spermatogonia.Collated expression values from the FCA are provided in Supplementary Table 2. In many cases there is detectable expression of these genes in spermatogonia, although transcript abundance peaks in early spermatocytes.198: remove "distribution of".Fixed (line 200).311: enrichment relative to what?Fixed (line 313). It is relative to signal in wing discs.344: other aspects could be regulated such as elongation, termination.We have added caveats to our speculations in this sentence (lines 340-356). The increased signal we see in gene bodies could be due to slower RNAPII elongation, but we don’t see a way that changes in termination would produce this pattern.Drosophila vs mammals, and studies that indicate that MSCI does occur in Drosophila (DOI: 10.3390/genes12111796).369: This part of the paper seems overly speculative, given the many molecular differences between dosage compensation mechanisms of Drosophila, instead they argue that MSCI could be the force driving the evolutionary depletion of male-germline-expressed genes they describe. These and many studies in the literature have conflated the effects of a lack of X dosage compensation and of MSCI in the male germline. Our direct measurements of RNAPII in spermatocytes demonstrates that there is no dosage compensation nor is there MSCI. Further, profiling of histone modifications associated with Drosophila somatic dosage compensation (H4K16ac) or with mammalian MSCI  show that the molecular mechanisms found in these other settings are not in play in the Drosophila male germline. As we have established these biological differences between mammals and Drosophila, it is appropriate to now speculate on why these differences may be, which we do on lines 374-384.We disagree, and this is a central point in our manuscript. The paper referred to here does not directly assess MSCI in : Can the authors justify their assumption that chromatin features of larval wing disc cells will match those of somatic cells of adult testes?We don’t only compare germline features to somatic cells of the wing disc, but also to genes with somatic expression in the testes annotated by FCA expression data . Note in Supplementary Figure 2 the distribution of RNAPII in whole testes (which includes somatic cells) is similar to that of larval wing discs, confirming that the differences we describe are specific to germline cells.