ATRX loss couples genome instability at a G-rich repeat to dysregulation of human alpha-globin expression

Domain: neuroscience
Published: 2026-02-14
Editorial outcome: major_revision

Abstract
Germline mutations in the chromatin remodelling protein ATRX cause a severe developmental disorder associated with α-thalassemia. In addition, ATRX is amongst the twenty genes most frequently mutated in cancer. How ATRX mutations alter gene expression remains unclear. Using the α-globin locus as a model, here we show that ATRX deficiency downregulates α-globin in a subset of cells exhibiting DNA damage. A G-rich repeat at the α-globin locus serves as a potential site of G-quadruplex formation and DNA damage. ATRX binds this repeat co-transcriptionally, and its loss increases R-loop accumulation at this site, leading to local DNA damage and transcriptional disruption in cis. Deletion of this repeat abolishes this effect, while targeted DNA damage reinstates it. These findings reveal a mechanism linking ATRX’s role in genome stability to transcriptional regulation and uncover a molecular basis of human genetic disease mediated via a distal G-rich repeat.

Introduction
The ATRX gene was first identified because when mutated it causes a specific, severe form of syndromic intellectual disability associated with alpha-thalassaemia: so-called alpha-thalassemia X-linked intellectual disability (ATR-X) syndrome1. ATRX thus plays a key role in normal development2, and it is also one of the twenty genes most frequently mutated in cancer3–5. ATRX is a highly conserved SWI/SNF chromatin remodelling protein, which forms a multi-protein complex with the histone variant H3.3 and the histone chaperone DAXX to maintain chromatin organisation6–9. ATRX plays a part in many nuclear processes including DNA replication, transcription, DNA damage and DNA repair10–17. Although previous studies have mapped ATRX binding to heterochromatin, CpG islands, and active regulatory elements18–22, the precise mechanisms by which ATRX regulates gene expression remain unclear. Notably, ATRX selectively affects human alpha-globin (α-globin), but not beta-globin (β-globin) expression during erythropoiesis -- a process requiring coordinated expression of α- and β-globin genes to form haemoglobin heterotetramers (α2β2), providing a tractable model to explore its regulatory function.

In marked contrast to the β-globin cluster, the human α-globin cluster lies within an early replicating, GC-rich, gene dense, subtelomeric region of chromosome 16. The human α-globin genes are associated with prominent unmethylated CpG islands23,24 and are embedded within a region of the genome containing a high density of repeat sequences including several G-rich variable number tandem repeats (VNTRs) (Fig. 1a). In ATR-X syndrome, mutations in ATRX downregulate gene expression at the human α-globin locus, with the α-like globin gene HBM being most affected, followed by α-globin genes HBA2 and HBA119, suggesting a unique mechanism of gene regulation.

In this study, we investigate how ATRX loss leads to α-thalassemia, a key disease phenotype of ATR-X syndrome, by elucidating the mechanisms that link ATRX’s gene regulatory functions to human disease. Here we show that dysregulation of α-globin expression in the absence of ATRX depends on a G-rich VNTR within the human α-globin locus. Loss of ATRX promotes G-quadruplex (G4) and R-loop formation at this site, resulting in DNA damage and distance-dependent disruption of gene expression. Removal of this VNTR abolished the gene downregulation caused by ATRX loss and inducing DNA damage at this site restored the effect. Together, our findings uncover a systematic mechanism of ATRX-mediated gene regulation, highlighting its role in orchestrating genome stability and transcription regulation. In addition, by directly linking molecular dysfunction at tandem repeats to human pathology, our work reveals a pathogenic mechanism underlying human genetic disease, underscoring the clinical significance of genome stability and chromatin dynamics at repetitive loci.

Results
ATRX loss perturbs α-globin expression in a subset of cells
To unravel the underlying mechanism by which ATRX regulates α-globin expression, we established an ATRX-deficient model by inducing a knockout (KO) of ATRX, using CRISPR-Cas9, in CD34+ haematopoietic stem and progenitor cells (HSPCs) from healthy male donors. Cells were electroporated with ribonucleoprotein (RNP, Cas9 protein complexed with guide RNA) targeting either ATRX, or as a control, the safe-harbour locus AAVS1. These CD34+ cells were then differentiated into erythroid cells using a three-phase differentiation system25 for genotype and phenotype analysis (Fig. 1b). Genotype analysis detected an average of 84.7% indels and 72% of knockout (out-of-frame) effect (Supplementary Fig. 1a), and the abolishment of ATRX was confirmed at the protein level (Fig. 1c). Consistent with ATRX’s role in replication10,14,15, ATRX KO cells showed slightly lower cell proliferation (Supplementary Fig. 1b). Phenotypically, ATRX KO cells demonstrated normal erythroid differentiation (Supplementary Fig. 1c) and cellular morphology (Supplementary Fig. 1d). Haemoglobin analysis revealed a similar pattern to the controls, with dominant adult haemoglobin A (HbA) expression and minor fetal haemoglobin (HbF) expression (Supplementary Fig. 1e). As in the peripheral blood of many patients with ATR-X syndrome, ATRX KO cells only showed a very mild (non-significant) reduction in HBM expression (Fig. 1d) and no erythroid cells with haemoglobin H (HbH, β4) inclusions were found2.

The absence of an α-thalassemia phenotype in ATRX KO cells may be due to the ATRX defect affecting only a small subset of cells, which is often obscured in a bulk population analysis. To address this, early erythroid progenitors (EEP) cells were sorted (Supplementary Fig. 1f) and plated for a colony-forming unit (CFU) assay, which allowed us to determine the genotype and the pattern of gene expression in individual erythroid colonies. ATRX KO sample showed similar haematopoietic progenitor frequencies (Supplementary Fig. 1g) and colony-forming capacity (Supplementary Fig. 1h-i) as the AAVS1 control. Single burst-forming unit-erythroid (BFU-E) colonies were then manually picked and analysed for their genotype and gene expression. A total of 96 BFU-E colonies from the AAVS1 sample and 351 colonies from the ATRX KO sample were analysed. Out of the 351 collected colonies, 240 (68.38%) had frameshift (FS) indels (Fig. 1e). Fifty AAVS1 “edited” colonies and 190 colonies from the ATRX sample harbouring ATRX frameshift (FS) indels were randomly selected for Biomark gene expression analysis. This showed reduced ATRX expression in most ATRX_FS colonies, however, only a subset showed decreased HBM and HBA expression (Fig. 1f). As expected from previous work19, HBM was more affected than HBA (Fig. 1g). Together, these results indicate that as in the peripheral blood of ATRX patients20, loss of ATRX affects gene expression at the α-globin locus in only a subset of cells, and HBM is more affected than HBA.

scRNA-seq links the gene perturbation to DNA damage response
To uncover the associated molecular signatures in the affected cells and elucidate ATRX’s regulatory mechanisms, we next performed single-cell RNA sequencing (scRNA-seq) on AAVS1 and ATRX KO cells. Characterisation during erythroid differentiation identified day 13 as optimal for single-cell analysis, in that ATRX KO cells showed pronounced HBM downregulation with a 77% knockout efficiency (Supplementary Fig. 2a-c). Accordingly, single day 13 nucleated erythroid cells were sorted for Smart-seq2 analysis (Supplementary Fig. 2d). After quality filtering and identification of highly variable genes (HVGs), principal component analysis (PCA) and t-distributed stochastic neighbour embedding (t-SNE) were performed. Both analyses indicated a closely overlapping distribution pattern between ATRX KO cells and the controls (Fig. 2a, Supplementary Fig. 2e). Differential gene expression analysis identified only 53 differentially expressed genes (DEGs) that were significantly downregulated, including HBM, and 18 upregulated genes (Fig. 2b, full list provided in Supplementary Data 1). Gene Ontology (GO) analysis of these DEGs highlighted pathways related to cell cycle, cell division, and erythrocyte function (Supplementary Fig. 2f), consistent with ATRX’s roles in facilitating DNA replication10,14,15 and the observation of slower proliferation of ATRX KO cells in culture (Supplementary Fig. 2a). Of interest, RNF168, a key DNA damage response regulator, was significantly upregulated in ATRX KO cells (Fig. 2b-c), suggesting increased DNA damage in the absence of ATRX. The MRN-ATM-γH2AX-RNF168 pathway is essential for DNA damage response and repair26. ATRX has previously been shown to interact with the MRN complex to overcome replication stress and facilitate DNA repair14. To assess DNA damage in ATRX KO cells, we performed immunofluorescence staining for phosphorylated H2AX (γH2AX) and observed an increased number and intensity of γH2AX foci compared to the controls, indicating elevated DNA damage following ATRX loss (Fig. 2d).

To look into the transcriptomic signature of the affected subpopulation, cells were categorised based on globin gene expression. As a group, the ATRX KO sample showed similar levels of α-globin (HBA), β-globin (HBB), and γ-globin (HBG) expression to AAVS1 control but significantly reduced α-like-globin HBM expression (Fig. 2e). However, scatter plots revealed a subpopulation of ATRX KO cells at quiescent G1 phase with low α(-like)-globin expression (HBM and HBA) but normal HBB expression (Fig. 2f, Supplementary Fig. 3a-b), indicating this subpopulation of cells exhibited α-thalassemia. This enables us to group cells into HBM low, HBM mid and HBM high based on their HBM expression (HBM low < 2.5, HBM high > 7) (Supplementary Fig. 3c), with HBM low exhibiting more separated clustering in the tSNE plot (Supplementary Fig. 3d). DEG and GO analysis between HBM high and HBM low cells (Supplementary Fig. 3e) identified 56 downregulated pathways exclusively in the HBM low ATRX KO cells (Supplementary Fig. 3f, Supplementary Data 2). The analysis also indicated 5 upregulated pathways exclusively in the affected HBM low ATRX KO cells (Supplementary Data 2), including mitochondrial dysfunction, cell responses, and importantly, histone H2A ubiquitination pathways (Fig. 2g). Interestingly, histone H2A is the primary histone substrate of RNF168 and closely associated with transcriptional silencing27. To validate whether H2A ubiquitination is dysregulated in ATRX KO cells, immunofluorescence staining for ubiquitinated H2A (H2Aub) was performed. A subset of ATRX KO cells exhibited increased H2Aub intensity, indicating activation of the DNA damage response pathway (Fig. 2h). Consistently, UIMC1 (encoding RAP80), a ubiquitin-binding protein that recognises ubiquitinated histones at DNA damage sites28, was significantly upregulated in the affected ATRX KO HBM low subpopulation (Fig. 2i, Supplementary Fig. 3g). Collectively, these findings suggest ATRX loss leads to increased DNA damage and enhanced RNF168-mediated H2A ubiquitination, which may contribute to the repression of genes lying within or adjacent to regions of DNA damage.

ATRX regulates gene expression at the α-globin locus via a G-rich VNTR
A potential site of DNA damage at the human α-globin locus is a highly repetitive VNTR region with 96% GC content, located within the second intron of the pseudogene HBZP1. This is located approximately 1 kb upstream of HBM, 8 kb upstream of HBA2, 12 kb upstream of HBA1 and is referred to as the pseudo-zeta (ψζ) VNTR (Fig. 1a). This VNTR comprises highly G-rich repeats (CGCGGGGCGGGG) that can form G4 structures in vitro19,29, making it a prime candidate for causing DNA damage at the α-globin locus in the absence of ATRX. Of importance, we have previously shown that the size of ψζ VNTR positively correlates with the degree of α-globin downregulation in patients with ATR-X syndrome19. This led us to hypothesise that the ψζ VNTR acts as a transcriptional modulator of human α-globin expression regulated via ATRX. Of interest, this VNTR is absent in the mouse genome and ATRX deficiency in mouse models of ATR-X syndrome do not have α-thalassaemia30.

Using a well-established human model to study erythropoiesis (HUDEP-2 erythroid progenitor cell line), we tracked ATRX binding at the ψζ VNTR during erythroid differentiation. ATRX ChIP-seq demonstrated that ATRX starts to bind at the ψζ VNTR on day 4 of differentiation coincident with the onset of transcription of the zeta (ζ) pseudogene HBZP1 and α-like-globin gene HBM (Fig. 3a-c). This binding pattern, correlated with transcriptional activation, aligns with prior evidence of ATRX associating with G-rich sequences when they are transcribed31. To study the influence of the ψζ VNTR on α-globin gene expression, we first generated an inducible ATRX degron system in HUDEP-2 cells (Fig. 3d) and subsequently knocked out the ψζ VNTR. Characterisation of the ATRX degron cell line indicated normal erythroid differentiation, even under dTAG-13 treatment (Supplementary Fig. 4a-b). dTAG-13 induced rapid and potent degradation of ATRX (Fig. 3e, Supplementary Fig. 4c). As expected, this was associated with a significantly reduced level of HBM expression and slightly decreased HBA expression (Fig. 3f, Supplementary Fig. 4d), faithfully mimicking the mild α-thalassaemia phenotype seen in ATR-X syndrome. To test whether the degradation of ATRX downregulates α-globin expression via an effect on the ψζ VNTR, we next generated a HUDEP-2 cell line in which the ψζ VNTR was deleted from both alleles via CRISPR-Cas9 (Supplementary Fig. 5a) and repeated the dTAG experiment. The VNTR KO line showed normal erythroid differentiation (Supplementary Fig. 5b-c), and ATRX can be potently degraded by dTAG-13 (Fig. 3e). Interestingly, in striking contrast to the previous experiment, when the ψζ VNTR was removed, HBM was no longer downregulated in the absence of ATRX (Fig. 3f), showing that downregulation of HBM expression in the absence of ATRX is mediated via the G-rich ψζ VNTR.

G4s, R-loops, and DNA damage at G-rich VNTRs drives gene dysregulation
The ψζ VNTR is predicted to form highly stable G4 structures (G4Hunter32,33 score > 2) (Supplementary Fig. 6a). Treating cells with G4 stabilisers during day 6 to 8 of differentiation revealed that CX-5461 specifically downregulated HBM expression to levels comparable to that seen when ATRX is absent, but had little effect on the β(-like)-globin genes HBB and HBG (Fig. 4a, Supplementary Fig. 6b). A similar downregulation of gene expression was observed at another ATRX target gene, NME4 (Supplementary Fig. 6b), which also contains a G-rich VNTR predicted to form a highly stable G4 structure (G4Hunter score > 2) (Supplementary Fig. 6c). To assess whether this represents a broader phenomenon, we examined the 71 genes dysregulated in CD34 ATRX knockout cells for the presence of GC-rich repetitive elements. Notably, 45 of 71 genes (63.4%) contained GC-rich tandem or low-complexity repeats (Supplementary Data 1), which is significantly higher than the genome-wide background rate of such repeats (23.3%, analysis based on the UCSC RepeatMasker track, p < 1 × 10-15; one-tailed binomial test). This suggests a general mechanism by which the absence of ATRX perturbs the expression of genes associated with such sequences. Consistent with this, when the ψζ VNTR was deleted, CX-5461 no longer had effect on HBM expression (Fig. 4a) but retained its effect on NME4 expression (Supplementary Fig. 6b), implicating the formation of G4 structures at the ψζ VNTR in HBM regulation.

It has previously been shown that ATRX binds to known G4 structures when they are transcribed and that accumulate R-loops which stabilise such structures31,34. In line with this, ATRX-deficient cells displayed a genome-wide increase in R-loops (Fig. 4b). DNA:RNA IP (DRIP)-qPCR further revealed significantly elevated R-loop formation at the ψζ VNTR locus in the absence of ATRX (Fig. 4c). Interestingly, overexpression of RNase H in ATRX-deficient cells partially restored HBM downregulation (Fig. 4d), supporting a functional role for R-loops in regulating HBM transcription. Accumulated G4 structures and R-loops are known to cause replicative stress and DNA damage, leading to perturbed chromatin and local transcriptional silencing35–37. Hence, we proposed that ATRX depletion induces the formation of unusual secondary structures at the ψζ VNTR, which triggers DNA damage and downregulates the nearby α(-like)-globin genes (HBM and HBA).

To test whether DNA damage alone could drive HBM dysregulation, we introduced local DNA double-strand breaks (DSBs) upstream of HBM via CRISPR-Cas9 targeting in the region where the ψζ VNTR had been deleted (VNTR KO cells) (Fig. 4e). Interestingly, this artificially induced DNA damage led to marked downregulation of HBM and, to a lesser extent, HBA expression (Fig. 4f). This suggests that downregulation of HBM and HBA gene expression and the consequent alpha-thalassemia occurs in cis as a result of DNA damage at the ψζ VNTR. It has been previously reported that transcription is highly repressed at sites adjacent to DSBs, and that this repression decreases upon movement away from the lesion38,39, as shown at the α-globin locus (HBM > HBA2 > HBA1)19. The mechanism appears to be complex40, but the α-globin locus model presented here offers the opportunity to solve this in detail.

Methods
CD34+ cell culture and differentiation
The CD34+ cells were separated from healthy adult peripheral blood leucocyte cones purchased from the National Health Service Blood and Transplant (NHSBT), UK. Ethical approval was granted by the Wales Research Ethics Committee (REC5) (13/WA/0371). The mononuclear cells were isolated using Histopaque-1077 (Sigma, Cat No H8889), and CD34+ cells were purified using Human CD34 Microbead kit (Miltenyi Biotec, Cat No 130-046-702) following the manufacturer’s instruction and the purity was confirmed by by FACS. The CD34+ cells were cultured in StemSpan SFEM II media (StemCell Technologies, Cat No 9655) supplemented with 100 ng/mL SCF (PeproTech, Cat No 300-07), 100 ng/mL TPO (PeproTech, Cat No 300-18), 100 ng/mL Flt3L (PeproTech, Cat No 300-19) and 1x Penicillin/Streptomycin (P/S, Gibco, Cat No 15070063) for 24 hours at 37°C with 5% CO2 incubation prior to electroporation. After electroporation, the cells were recovered in the same media without P/S for 24 hours before starting erythroid differentiation.

CD34+ cells were differentiated along the erythroid lineage using a previously described three-phase liquid culture system25, requiring a base media Iscove’s Modified Dulbecco’s Medium (IMDM) (Gibco, Cat No 31980022) containing 3% Solvent/Detergent pooled Human AB plasma (NHSBT), 10 μg/mL human insulin (Merck, Cat No I9278), 3 U/mL heparin (Merck, Cat No H3149), 3 U/mL erythropoietin (EPO, Oxford University Hospital (OUH) pharmacy), 200 μg/mL iron saturated human holo-transferrin (Bio-Techne, Cat No 2914-HT), 2% (v/v) fetal bovine serum (FBS) and 1x P/S. In phase I (day 0 to day 7), 1 ng/mL IL3 (PeproTech, Cat No 200-03) and 10 ng/mL SCF were added. In phase II (day 7 to day 11), the IL3 was removed and only 10 ng/mL SCF was supplemented. In phase III (post day 11), only 300 μg/mL holo-transferrin was added. The media was changed every two days to maintain cell concentration around 1-2 × 10^5 cells/mL in phase I and phase II, 0.5-1 × 10^6 cells/mL in phase III.

CRISPR-Cas9 knockout experiment in CD34+ cells
Given that ATRX is located on the chromosome X and ATR-X syndrome only affect males, donor gender was confirmed by checking the SRY gene on chromosome Y. Only CD34+ cells derived from the male donors were used for CRISPR experiment to achieve efficient ATRX knockout given the ATRX gene is located on chromosome X. 1-3 × 10^5 of CD34+ cells were transfected with RNPs (3.2 μg sgRNA (synthesised by Synthego) + 6 μg SpCas9 nuclease (IDT)) using Amaxa P3 Primary cell 4D-Nucleofector X Kit (Lonza, Cat No V4XP-3032) and 4D-Nucleofector X Unit device (Lonza). Guide RNA sequences are listed in Supplementary Table 1. Cells were recovered in pre-warmed antibiotic-free SFEM II complete media right after the electroporation for 24 hours before the initiation of differentiation or cell sorting. ATRX knockout efficiency was assessed by Sanger sequencing of the targeted region using primers listed in Supplementary Table 1, followed by Synthego Inference of CRISPR Edits (ICE) analysis.

Colony forming unit assay
CFU assay was performed following the technical manual for Human CFU Assays. Using MethoCult (STEMCELL Technologies, Cat No H4435). Single-cell suspensions were prepared and diluted in Iscove’s MDM supplemented with 2% FBS medium (STEMCELL Technologies, Cat No 07700) and then mixed into enriched MethoCult (STEMCELL Technologies, Cat No H4435) to allow progenitor cells to expand and differentiate into colonies under incubation at 37°C with 5% CO2. After 14-16 days of culture, colonies were examined and scored based on their morphology. Then the single individual BFU-E colonies were manually picked under a light inverted EVOS XL Imaging System (ThermoFisher Scientific, Cat No AME3300) and transferred into tubes containing cold PBS. Each collected colony sample was subsequently divided into two aliquots - one for genotyping after whole genome amplification and the other for gene expression analysis using the Fluidigm Biomark system.

Analysis of single BFU-E colonies
Genomic DNA from single BFU-E colonies was amplified directly from cell lysate using Illustra Single Cell GenomiPhi DNA Amplification Kit (GE Healthcare, Cat No 25-6600-30) following the manufacturer’s instructions. Then PCR amplification of CRISPR target regions and subsequent Sanger sequencing were conducted using the purified DNA to determine their genotype.

For gene expression analysis, samples were mixed with 2x Reaction Mix containing Superase-In and cDNA was pre-amplified by adding 0.2x Taqman assay mix and RT/Taq mix (from Superscript III One Step Kit, ThermoFisher, Cat No 12574026). The amplification was carried out on a Bio-Rad T100 Thermal Cycler under the following conditions: 50°C for 15 minutes, 95°C for 2 minutes, followed by 20 cycles of 95°C for 15 seconds and 60°C for 4 minutes. The resulting cDNA was diluted with 4x vol TE buffer and stored at −20°C for up to 3 months. Then the diluted cDNA and Taqman Assays were loaded onto an IFC chip for gene expression analysis as per protocols provided on the Fluidigm website. Data analysis was finished using the built-in software, adhering to the “Real-Time PCR Analysis” guidelines from Fluidigm. Colonies with undetected reference genes were excluded from further analysis. For gene expression analysis of ATRX, HBA and HBM in individual BFU-E colonies, expression values were normalised to the mean of reference genes (RPL13A, RPS18, ACTB and GAPDH), and a uniform cutoff of 2 was applied to relative expression values during plotting to exclude outlier values.

Cellular morphological analysis - Wright’s stain of cytospin
1 × 10^5 cells were resuspended in 200 μL of PBS, spun (400 rpm for 5 mins) onto a glass slide in a Cytospin 4 Centrifuge (ThermoFisher). The slides were air-dried, stained with modified Wright’s Stain using Hemateck slide strainer and mounted in DPX (Sigma, Cat No 06522). Cytospins were imaged using an Olympus BX60 microscope.

Flow cytometry
Cells were washed and resuspended in 100 μL of FACS buffer (1x PBS supplemented with 2% FBS and 2 mM EDTA) prior to staining with a panel of fluorophore-conjugated antibodies at 4°C for 30 min. Following antibody staining, the cells were washed and resuspended in FACS buffer containing Hoechst-33258 for live/dead cell analysis. FACS analysis was done on an Attune NxT analyser (ThermoFisher). Gating was set using fluorescence-minus-one (FMO) and unstained controls. Analysis was performed using FlowJo software. The details of the FACS panels and flow cytometry antibodies are provided in Supplementary Table 2.

Iso-electric focusing for haemoglobin analysis
Approximately 5 × 10^5 cultured erythroblasts were lysed in haemoglobin elution solution, and the haemoglobin was analysed using an iso-electric focusing kit (RESOLVE Haemoglobin kit, PerkinElmer, USA) on a water-cooled horizontal electrophoresis rig (GE Healthcare) according to the manufacturer’s instructions. Following electrophoresis, the gels were fixed in 10% trichloroacetic acid and stained using the JB-2 staining system (PerkinElmer, USA) as per the manufacturer’s guidelines.

HUDEP-2 cell culture and differentiation
Wild type HUDEP-2 cells were obtained from the Cell Engineering Division, RIKEN BioResource Center, Tsukuba, Japan64. During the expansion phase, cells were cultured in StemSpan SFEM medium (STEMCELL Technologies, Cat No 09650) supplemented with 50 ng/mL SCF, 3 U/mL EPO, 0.4 μg/mL dexamethasone (OUH pharmacy), 2 mM L-Glutamine (Gibco, Cat No 25030081), 1x P/S, and 2 μg/mL doxycycline (Sigma-Aldrich, Cat No D9891). Cultures were maintained at 37°C 5% CO2 incubator, with a cell density of 0.5-1 × 10^6 cells/mL. The media was replaced every two days to ensure an effective doxycycline concentration.

Differentiation of HUDEP-2 cells used a two-phase liquid culture system, requiring a base media consisted of IMDM supplemented with 3% Human AB plasma, 10 μg/mL human insulin, 3 U/mL heparin, 3 U/mL EPO, 200 μg/mL holo-transferrin, 2% (v/v) FBS and 1x P/S. From day 0 to day 6, 1 ng/mL IL3, 50 ng/mL SCF, and 2 μg/mL doxycycline were added to the base media for cell differentiation. After 6 days, media was changed to the second phase, where only 300 μg/mL holo-transferrin was supplemented to the base media. Media was changed every two days. Cell density was maintained at 1 × 10^6 cells/mL prior to day 6 and at 1.5 × 10^6 cells/mL thereafter.

Generation of ATRX degron cell line
A guide RNA targeting the ATRX C-terminal domain (CTD) (gRNA sequence in Supplementary Table 1) were designed and cloned into the pX458-Ruby plasmid (Addgene 110164). A DNA donor template for homologous-directed recombination (HDR) was constructed to contain EGFP-FKBP12F36V, flanked by 800 bp homologous arms on each side, directly linking to the absolute CTD of ATRX. The donor DNA was synthesised and inserted into pMK-RQ plasmid. To prevent cleavage of the donor DNA, all sgRNA target sites within the donor plasmid were point-mutated without altering the encoded amino acids. For nucleofection, 2.5 μg of the pX458-Ruby-gRNA plasmid and 2.5 μg of the donor plasmid were co-transfected into 2 × 10^6 HUDEP-2 WT cells using the 2B Amaxa Human CD34 Cell Nucleofector Kit (Lonza, Cat No VPA-1003) on the AMAXA Nucleofector 2B system following the manufacturer’s instructions. The transfected cells were cultured in HUDEP-2 SFEM expansion media supplemented with 0.75 μM RAD51-stimulatory compound-1 (RS-1) to enhance HDR efficiency. Two days post-transfection, Ruby+ cells were bulk sorted to recovering for 1 week and subsequently single-cell sorted into Terasaki plates (Nunc, Cat No 163118) for clonal screening. Successful grown clones were genotyped using the primers listed in Supplementary Table 1.

Generation of ATRX degron-ψζ VNTR KO cell line
The ψζ VNTR region was knocked out in the ATRX degron cell line using a dual-gRNA CRISPR-Cas9-mediated knockout strategy. Due to the high homology between HBZ and its pseudogene HBZP1 where ψζ VNTR resides, the 5’ sgRNA was designed to target HBZP1 promoter where the sequences have no homology with HBZ, while the 3’ sgRNA targeted a downstream region of HBZP1. This design facilitated the deletion of the entire HBZP1 (~2.5 kb). The dual gRNAs were cloned into the pX458-eGFP (Addgene 48138) and pX458-Ruby (Addgene 110164) plasmids respectively, and 2.5 μg of each was co-transfected into 2 × 10^6 ATRX degron cells using the same nucleofection protocol as described above. Cells were cultured in SFEM expansion media after transfection, and GFP+ Ruby+ double-positive cells were sorted prior to single clonal screening via a PCR-based strategy. The gRNA and primer sequences used are provided in Supplementary Table 1.

RNA extraction and qPCR
0.5-2 × 10^6 cells were collected in 350 μL RLT buffer (from QIAGEN RNeasy Mini Kit), snapped frozen on dry ice and stored at −80°C until use. Total RNA was purified using RNeasy mini kit (QIAGEN, Cat No 74104), and 1 μg of total RNA was used to generate complementary DNA (cDNA) using SuperScript III First Strand Synthesis SuperMix (ThermoFisher, Cat No 11752-250). All quantitative reverse transcription PCR (qRT-PCR) were carried out using inventoried TaqMan assays (Applied Biosystems; TaqMan IDs: HBA2/HBA1-Hs00361191_g1, HBB-Hs00747223_g1, HBG-Hs00361131_g1, HBM-Hs01392876_g1, NME4-Hs00359037_m1, RPL13A-Hs03043885_g1, RPS18-Hs01375212_g1, ACTB-Hs01060665_g1, GAPDH-Hs02758991_g1) and Taqman Universal PCR Master Mix II (ThermoFisher, Cat No 4440040) in technical triplicate on StepOnePlus Real-Time PCR System (Applied Biosystems). Data were first analysed using the delta-delta CT (ΔΔCT) method and then normalised to the control sample. For PCR amplification of pseudo-zeta gene HBZP1, cDNA from HUDEP-2 WT cells was used as template and primers targeting zeta gene HBZ and pseudo-zeta gene HBZP1 (listed in Supplementary Table 1) were used to distinguish the specific amplification of HBZP1. The PCR reaction was carried out using PWO polymerase (Roche, Cat No 11644947001) and Platinum Taq (Invitrogen, Cat No 10966018), with the addition of Applied Biotechnologies Buffer IV (1x), 20 mM MgCl2, and a high G/C enhancer (1x, New England Biolabs, Cat No B9028) to overcome the high GC content and repetitive nature of the template. The thermal cycling conditions were as follows: 94°C for 2 min, 35 cycles of 94°C for 1 min, 60°C for 30 s, 72°C for 1 min 30 s and 72°C for 10 min.

Immunofluorescence staining
Cells were seeded on Cell-Tak (Corning, Cat No 354240)-coated Cell-View slides (Greiner Bio-One, Cat. No. 543978), and then fixed with 4% paraformaldehyde for 10 minutes, permeabilised with 0.1% Triton X-100 for 5 minutes, and blocked with 1% bovine serum albumin + 2% goat serum for 1 hour at room temperature. Cells were next incubated overnight at 4°C with an anti-γH2AX antibody (Merck, Cat. No. 05-636, use at 1:400) or anti-ubiquityl-histone H2A antibody (Cell Signaling Technology, Cat. No. 8240, use at 1:800). The following day, cells were incubated with Alexa Fluor 647-conjugated secondary antibodies for 1 hour at room temperature, followed by staining with DAPI. Fluorescence images were acquired using a Leica DMi8 Thunder microscope and analysed in Fiji software.

Protein extraction and western blot
At least 1 × 10^6 cells were lysed in 50-200 μL of RIPA buffer (Sigma, Cat No R0278) supplemented with digitonin (ThermoFisher, Cat No BN2006), Benzonase (Merck, Cat No 71205-3), and protease inhibitor cocktail (Roche, Cat No 11836153001), based on the cell number. Cells lysis was conducted for 40-60 minutes at 4°C on an end-to-end rotator. The lysate was centrifuged at 16,000 g for 10 min at 4°C. Supernatant was collected and mixed with an equal volume of 2x Laemmli Sample Buffer (Bio-Rad, Cat No 1610737) containing 1/4 volume of 1 M DTT (ThermoFisher, Cat No R0861).

Protein samples were denatured at 95°C for 5 minutes, chilled on ice, and loaded onto a NuPAGE Bis-Tris gel (ThermoFisher Scientific) using a Mini-PROTEAN system (Bio-Rad). Proteins were then transferred to a PVDF blotting membrane (Merck, Cat No 03010040001) overnight (14-18 hours) with constant 25 mA current, followed by blocking with 5% skimmed milk (Merck, Cat No 70166) dissolved in TBS-T (Tris buffered saline + 0.1% Tween-20). The membrane was incubated with primary antibodies for 1 hour at room temperature in 2.5% skimmed milk, washed three times with TBS-T, and then incubated with secondary antibodies for 1 hour at room temperature. After three additional washes, the membrane was exposed on X-ray film. Antibodies used in this study include: anti-ATRX (homemade mouse antibody, clone 39f; and Abcam, Cat No ab97508, use at 1:1000), anti-alpha tubulin (Abcam, mouse monoclonal, ab7291, use at 1:20,000), and HRP-conjugated secondary antibodies Goat anti-mouse IgG (ThermoFisher, Cat No 31430).

Smart-seq2 single cell RNA sequencing
CD34 differentiated day 13 erythroid cells were stained with the viability dye Hoechst33342 (ThermoFisher, Cat No 62249) before cell sorting. Single live nucleated cells were sorted into each well of a cold 384-well PCR plate (FrameStar 4titude, Cat No 4ti-0384/C) containing 2 µL of lysis buffer with barcoded Oligo(dT) (0.2% Triton X-100 (Sigma), 2 U/μl of RNase inhibitor (TaKara, Cat No 2313A), 2.5 mM dNTP, 0.025 AU/mL protease, and ERCC RNA spike-in)65 using a Sony SH800S Cell Sorter. Next, retrotranscription and PCR steps were performed65. Briefly, proteinase in the lysis buffer was heat-inactivated at 72°C for 15 min, during which retrotranscription mix was prepared by mixing SMARTScribe retrotranscriptase (Clontech, Cat No 639537), RNase inhibitor, and template-switching oligo TSO-LNA (sequence: AAGCAGTGGTATCAACGCAGAGTACATrGrG+G, RNase-free HPLC purified). The RT mix was dispensed into each well after heat inactivation and first-strand cDNA was synthesised. Afterwards, the cDNA was amplified by SeqAMP (Clontech, Cat No 638509) using 21 PCR cycles. Amplified products from each plate were pooled, bead-purified, tagmented, and indexed using Tn5 enzyme (Illumina Nextera XT Kit, Cat No FC-131-1096) to construct libraries. The libraries were purified with AMPure beads, assessed on TapeStation System (Agilent), quantified using the NEBNext Library Quant Kit (NEB, Cat No E7630L), and sequenced on a NextSeq platform with 75 bp single-end reads using the NextSeq 500/550 High-output 75 Cycle Kit (Illumina, Cat No 20024906).

scRNA-seq data analysis
Demultiplexed FASTQ files were trimmed for polyA tails using Trim-Galore; files from different lanes were merged using samtools and aligned to hg19 genome using STAR. Gene counts for each cell were obtained with FeatureCounts and normalised by dividing total library size of the cell and multiplying by the mean library size across all processed cells. Genes with normalised counts <1 were considered non-detected and their expression values were set to 0. The normalised counts were further applied with log2 normalisation. QC filtering was performed to retain cells with >3000 reads; <10% mitochondrial reads, and >70% mapped reads per cell. Highly variable genes were identified by fitting a LOESS model of log2(mean expression) versus coefficient of variation for each gene. Genes with a coefficient of variation above the fitted model and log2(mean expression) ≥ 0 were selected as HVGs. Dimensionality reduction was performed by PCA (20 dimensions) and t-SNE (‘Rtsne’ package, with “perplexity=10, max_iter=500”) using HVGs, and plotted using “ggplot2” package in R. Differentially expressed genes were identified using a non-parametric Wilcoxon test and expressing cell frequency was computed using Fisher's exact tests on log2-normalised counts for genes expressed in ≥ 5 cells. Significant genes were defined by an adjusted p value (false discovery rate (FDR) < 0.05) and an absolute log2 fold change (|log2FC| > 0.5). P values were combined using Fisher’s method, and adjusted p-values were calculated using the Benjamini & Hochberg FDR procedure. Violin plots from selected genes were generated using “ggplot2” package in R. GO analysis was conducted using ClusterProfiler R package. Differentially expressed gene set was compared with the gene list from org.Hs.eg.db from the Bioconductor package for GO analysis with settings ont=“BP”, pAdjustMethod=“fdr”. For cell cycle analysis, a Seurat object was created using the original count table. Cell cycle scores were computed and used to assign cell cycle stages. Fisher’s test was used to examine cell cycle difference between groups.

Chromatin Immunoprecipitation sequencing (ChIP-seq) and data analysis
ATRX ChIP was performed on 5 × 10^7 cells using the ChIP Assay Kit (Millipore, Cat No 17-295) following an optimised protocol20,45. Briefly, cells were double-fixed with firstly 2 mM ethylene glycol bis(succinimidyl succinate) (EGS, Sigma, Cat No E3257) for 45 min and then 1% formaldehyde solution for 20 min at room temperature. The cross-linking was quenched with 125 mM glycine (Sigma-Aldrich, Cat No G7126). After cells lysis, the chromatin was fragmented using Covaris ME220 ultrasonicator (Peak Incident Power (PIP): 75, Duty factor (DF): 14, Cycles/burst (cpb): 1000, Duration: 900 s, Temp: 6°C), followed by pre-clearing with Protein A/G Dynabeads (Invitrogen, Cat No 10001D, 10003D) before immunoprecipitation with 15 μg ATRX antibody (Abcam, Cat No ab97508). After sequential washes at 4°C, samples were eluted, de-crosslinked and proteinase K treated. DNA was precipitated using phenol/chloroform extraction and ethanol precipitation with GlycoBlue (15 mg/mL) (Thermo Scientific, Cat No AM9516) prior to dissolving in 20 μL of ultrapure water. DNA was quantified using the Qubit dsDNA HS assay (Invitrogen, Cat No Q32854) and indexed using NEBNext Ultra II DNA library prep kit (NEB, Cat No E7645L). Libraries were quantified, and sequenced on an Illumina NextSeq machine with paired-end reads.

ChIP-seq data quality was assessed by FASTQC. Data was analysed using a customised in-house pipeline (https://github.com/Hughes-Genome-Group/NGseqBasic/releases). Paired-end reads were aligned to the hg19 genome using bowtie2. Output BAM files were sorted and indexed using Samtools, normalised to RPKM using Deeptools (--normalizeUsing RPKM), and converted to BigWig files for visualisation in the USCS genome browser. BigWig files were used for peak calling on LanceOtron (https://lanceotron.molbiol.ox.ac.uk/).

CRISPR-Cas9-induced DNA damage assay
2 × 10^6 of ATRX degron-VNTR KO differentiated day 6 cells were transfected with RNPs using the 2B Amaxa Human CD34 Cell Nucleofector Kit on the AMAXA Nucleofector 2B system. Following electroporation, cells were cultured in HUDEP-2 day 6 differentiation media for 2 days before being harvested for qPCR analysis. Three different sgRNAs were tested individually, and their sequences are provided in Supplementary Table 1.

DRIP-qPCR
The DRIP protocol was performed as previously described66. 1 × 10^8 cells were harvested followed by nuclear lysis. Nuclear extracts were incubated with 30 mg proteinase K at 37°C overnight, followed by DNA isolation. To minimise nonspecific RNA signals detected by the S9.6 antibody, nuclei were pre-treated with RNase I at 2 U per 100 μg for 15 minutes at 37°C and sonicated to 200-300 bp. Half the fragments were treated with RNase H (Roche) at 10 U per 100 μg overnight at 37°C. Treated and untreated samples underwent S9.6 antibody immunoprecipitation and enrichment using sheep anti-mouse IgG Dynabeads (ThermoFisher Scientific, Cat No 11031). Hybrids were extracted with phenol/chloroform, precipitated with glycogen, and resuspended in nuclease-free water. qPCR analysis was performed on the samples to detect enrichment around ψζ VNTR and a distal region on chromosome 16. The qPCR run was done using SYBR Green master mix with primers listed in Supplementary Table 1.

Dot blot analysis of R-loops
Briefly, nuclear DNA were extracted from ATRX degron cells (treated with dTAG-13-neg or dTAG-13) by potassium acetate and ethanol precipitated. Precipitated DNA was gently spooled and washed with 70% ethanol without centrifugation. DNA was allowed to air dry before resuspended in water followed by brief sonication to reduce DNA viscosity. DNA concentration was measured and adjusted to 400 ng/μl, followed by serial dilutions. For RNase H controls, an aliquot of DNA was incubated with 5 U RNase H (M0297S New England Biolabs) in 0.5 M NaCl (EN0531 Thermo Scientific) at 37°C for 20 min respectively, then serially diluted. Two microliters of each dilution were spotted on a Hybond-N+ nylon transfer membrane (RPN203B Amersham), air-dried and UV-crosslinked. The membrane was then blocked with 5% milk overnight, followed by a 2 h incubation with anti-R-loop antibody S9.6 at 4°C before washing, and then incubated with HRP-conjugated secondary antibody. Signals were detected using enhanced chemiluminescence (ECL) kit (P90720 Millipore).

RNase H overexpression assay
Three million of differentiation day 6 ATRX degron cells (with dTAG-13-neg or dTAG-13 treatment) were electroporated with 3 μg of either a plasmid expressing GFP-tagged RNase H1 or a GFP alone control plasmid using Lonza Human CD34+ Cell Nucleofector Kit (Cat No VPA-1003) on the AMAXA Nucleofector 2B system. GFP+ cells were sorted after 12 h for RNA extraction using RNeasy micro kit (QIAGEN, Cat No 74004), followed by qRT-PCR analysis.

Statistical analysis
Statistical analyses between two groups were conducted using a two-tailed unpaired Welch’s t-test for normally distributed data, or the Mann-Whitney U-test for non-normally distributed data. Comparisons among three or more groups were performed using one-way ANOVA followed by Dunnett test. For datasets involving multiple conditions across groups, two-way ANOVA followed by Šídák’s test was applied. For all the fold-change data, relative fold-change values were log2-transformed before statistical analysis. Statistical significance was defined as p < 0.05, with significance levels represented as *p < 0.05, **p < 0.01, ***p < 0.001, and ****p < 0.0001. The number of independent experiments was indicated in each figure. Detailed descriptions of the statistical tests used for each dataset, along with exact p-values, are provided in the corresponding figure legends.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "This manuscript from Shen et al studies the role of ATRX in regulating transcriptional output from the a-globin locus. The\nmain conclusion of this work is that ATRX enhances expression of the a-like globin gene HBM by resolving R-loop formation\nand DNA damage at a G-rich variable number tandem repeat (VNTR) DNA sequence near the gene promoter. Overall, the\nconcepts presented are not novel per se, rather the strength of the study is that it confirms previous literature and presents a\nunified theory for ATRX function in regulating gene expression from the a-globin locus. The study itself is well done, using\ngenetic and chemical perturbation to probe the role of the VNTR in HBM expression. However, the conceptual advances are\nmodest, the scope in studying a single locus is limited, some claims are poorly supported, and some observations remain\nunexplained.\nThe work follows up on a seminal finding from the same lab that ATRX plays a role in regulating genes near tandem\nrepeats, with longer VNTRs resulting in a higher degree of gene downregulation upon ATRX loss (PMID 21029860). In the\ncurrent study, the authors use CRISPR gene editing tools to delete the VNTR proximal to HBM and demonstrate that HBM\nexpression is elevated and no longer dependent upon ATRX. This part of the study extends upon a study drawing similar\nconclusions for the HBM promoter in the context of a luciferase reporter assay (PMID 26991472). The current study goes on\nto link ATRX to G-quadruplex binding, R-loop formation, DNA damage, and transcription. Many studies in the literature have\ndemonstrated such connections (e.g., PMID 21029860, 25452430, 28487353, 30808951, 34162889, 35013239).\nOne conclusion from this work is that ATRX deficiency downregulates a-globin in a subset of cells exhibiting DNA damage.\nThis part of the work is poorly supported, and the authors do not definitively demonstrate that the cells exhibiting signs of\nDNA damage are the same cells downregulating a-globin transcription. Further, the authors do not explain why loss of\nATRX leads to stochastic changes in a-globin gene expression on a single cell level. These claims and observations\nrequire additional experimental support and analysis.\nSpecific Comments:\n1. The authors state that only a subset of ATRX KO BFU-E clones show decreased HBM and HBA expression. First, the\nauthors are missing callout to Extended Data Fig. 1j, which shows this relationship better than the box plots (where\ninformation about single cell behavior is lost) chosen for the main figure Fig. 1f. This point should be better represented in\nthe main figure, to show the expression level of HBM and HBA in individual BFU-E, compared to their ATRX expression\nlevel.\n2. Do all 53 downregulated genes in ATRX KO cells have VNTRs near their promoters or regulatory elements? Such\ngenome-wide analysis would help to expand the scope of the study and the impact of the conclusions.\n3. Lines 167-169 – links to DNA damage and HBM downregulation from the single cell data are weak. The argument is that\n(1) some ATRX KO cells have increased RNF168 expression; (2) some ATRX KO cells have increased gamma-H2AX\nstaining; and (3) some ATRX KO cells with low HBM expression show an ontology term for histone H2A ubiquitination\npathways. The authors have not confidently demonstrated that any of these observations are linked. Related, lines 313-315\nclaim in discussion that the work demonstrates increased H2A ubiquitylation in ATRX KO is overstated. The authors identify\nthis pathway as an ontology term but they do not directly measure H2AUb.\n4. The authors do not directly measure DNA damage at the a-globin VNTR in the absence of ATRX but rather make\ninferences that DNA damage of this locus plays a role in its transcriptional repression. The location of DNA damage in the\nabsence of ATRX should be assessed.\n5. Out of curiosity, what happened to tubulin at the 4 hr time point in Extended Data Fig. 4c?", "reviewer_2": "In this manuscript Shen et al examine ATRX function in gene regulation in an erythroid differentiation model. ATRX\nmutations are known to result in a mild form of alpha thalassemia. The goal of this paper is to develop a mechanistic\nunderstanding of ATRX function in this process. First the authors show that loss of ATRX results in reduced HBM\nexpression only in a subset of cells. They further perform single cell RNA seq to show deregulation in a subset of cells and\nthat a subset of these cells also exhibit gamma H2AX foci indicative of DNA damage. In addition RNA sequencing analysis\nshowed an upregulation of DNA damage response pathways. They develop a degron model where they can acutely deplete\nATRX in HUDEP2 cells. Using these cells they show that ATRX binds to the G-rich VNTR region at the alpha globin locus\nin a transcription dependent manner and that loss of ATRX results in reduced HBM expression. Effects of ATRX loss are\nattenuated by deletion of the VNTR region. Finally they show that the VNTR region accumulates R-loops in the absence of\nATRX. Interestingly introduction of DNA damage at these sites also recapitulates ATRX loss with respect to gene\nexpression.\nOverall this is a straightforward paper that is easy to follow and logical in narrative. However most of the conclusions of this\npaper have already been published previously by the same group or by several different groups in other journals as\nmentioned below. While the degron system itself is novel, there is very little novelty in the experiments performed using this\nsystem. Overall this manuscript does not contribute significantly to advancing our understanding of how ATRX regulates\ngene expression beyond what we know already.\nSpecific comments.\n1. Several groups have already shown that ATRX loss results in accumulation of DNA damage in different cell types. These\ninclude Wong et al in genome research 2010, Lovejoy et al plos genetics 2012, Huh et al JCI 2012. This is not new or\nunexpected.\n2. Gene ontology analysis in a small set of genes is not very informative or accurate. Presence of one or two gene in a\ncategory can point to the enrichment of a pathway. The same conclusions can be obtained by just looking at the gene\nnames.\n3. Fig 4 - Does DNA damage actually occur at the VNTR upon ATRX loss and R-loop accumulation? Some genomic\nmethod to evaluate this is needed.\n4. Fig 4c,d – Does inducing DNA damage cause R-loop formation at VNTRs given the recent reports of R-loops in DNA\ndamage repair?\n5. The title of the paper is misleading – it suggests that ATRX is able to resolve R-loops, when there is no evidence to\nsuggest that ATRX functions in unwinding R-loop or G4 structures.", "reviewer_3": "This study by Shen et al investigates the molecular mechanism by which mutations in the chromatin remodeler ATRX cause\nα-thalassemia, a feature of the developmental disorder ATR-X syndrome. The authors propose a multi-step mechanism for\nthe regulation of the α-globin gene: ATRX deficiency leads to the accumulation of R-loops and G-quadruplex (G4) structures\nat a specific G-rich variable number tandem repeat (VNTR) in the α-globin locus, which in turn induces local DNA damage\nand subsequent transcriptional silencing of the adjacent α-globin genes.\nThey employ complementary experimental systems including CRISPR-edited primary CD34+ hematopoietic stem cells and\nan inducible ATRX degron system in HUDEP-2 cells. The former approach allows for physiologically relevant analysis in\nprimary cells and the latter enabled temporal control of ATRX depletion. The scRNAseq analysis is particularly valuable, as\nit revealed the stochastic nature of the α-globin downregulation. The most compelling aspect of the study is the genetic\nrescue and recapitulation experiments.\nNevertheless, several weaknesses should be addressed:\n1-Several figures lack statistical testing or only show representative data without quantification. The sample sizes for some\nexperiments is low (some even at n=2) and appear limited for drawing any conclusion. The authors should include rigorous\nstatistics to all quantitative assays: replicate numbers (replicates should be biological rather than technical), adjusted p-\nvalues, and clear indication of the statistical tests used.\n2- While the paper establishes that ATRX loss leads to R-loop accumulation and subsequent DNA damage, it remains\nunclear whether ATRX primarily resolves R-loops, which then stabilize G4s, or acts on both independently. Additional\nexperiments, such as overexpressing RNase H1 to degrade R-loops, could clarify whether resolving R-loops alone prevents\nDNA damage and rescues α-globin expression.\n3- The authors suggest that the mechanism may be general, citing downregulation of NME4, another VNTR-containing\ngene. However, this is based on limited evidence. A genome-wide analysis of ATRX binding at G-rich repeats, R-loop\naccumulation, and transcriptional effects upon ATRX loss are required to support claims of broader relevance.\n4- The paper does not fully address why only a subset of ATRX-deficient cells exhibit the phenotype. Factors such as\ndifferences in transcription levels, replication timing, or pre-existing epigenetic states at the locus should be investigated to\nprovide deeper insight into the phenotype's variability. The authors should investigate whether transcriptional load,\nreplication timing or local chromatin marks or histone variants predict which ATRX-null cells become HBMlow.\n5- While the paper cites studies supporting its model of R-loop and G4-mediated DNA damage, it does not adequately\naddress alternative or conflicting mechanisms of ATRX-mediated α-globin regulation. For instance, the role of ATRX in\nhistone variant exchange, particularly the negative regulation of macroH2A incorporation at the α-globin locus, is well-\ndocumented in the literature. This study shows that ATRX loss leads to macroH2A accumulation at the HBA cluster,\ncontributing to transcriptional repression. Although the current paper briefly mentions histone H2A ubiquitination\npathways and cites Ratnakumar et al., 2012 in the discussion, it does not fully integrate or discuss this alternative pathway as a\npotential complementary or competing mechanism. A more explicit acknowledgment or comparison would improve the\nmanuscript.\n6- The temporal correlation between HBZP1 transcription and the appearance of an ATRX ChIP-seq peak at the ψζ VNTR,\non its own, is not sufficient to conclude that ATRX binding is transcription-dependent. Differentiation can potentially change\nmany variables—chromatin accessibility, histone modifications or variants, replication timing, DNA topology and the\nabundance of ATRX‐binding partners. Any one of these could, in principle, be the true driver of ATRX recruitment, with\nHBZP1 activation occurring in parallel.\n7- Several findings consolidate or refine previously reported associations and consequently the study provides important,\nbut at times incremental information (ATRX–VNTR binding, G4 propensity, macroH2A antagonism). The binding of ATRX at\nthis VNTR was previously reported. The G4 aspect has been described. The use of CX-5461 confirms, rather than\ndiscovers, the G4 component. MacroH2A and other epigenetic players are mentioned but not mechanistically explored;\nRatnakumar et al. already implicated macroH2A in α-globin repression after ATRX loss.", "reviewer_4": "In this manuscript, Shen et al. demonstrated that ATRX is an essential regulator for alpha-globin gene expression through\nresolving R-loop formation and preventing DNA damage at the G-rich VNTR located upstream of HBM gene. The pioneer\nwork from Dr. Higg’s lab revealed that in ATR-X syndrome, mutation of ATRX resulted in alpha-thalassemia through\ndownregulated alpha-globin genes. In this study, they provide a unique mechanism by which ATRX specifically regulates\nalpha-globin gene expression via preventing persistent R-loop formation in upstream of HBM gene. The manuscript is well\nwritten, and the conclusions are generally supported by the experiments conducted by the authors. However, there are some\ncomments that need to be addressed to strengthen and improve the manuscript.\n1. Figure 1 showed that ATRX KO efficiency is more than 70%, yet HBM is reduced only in very small fraction of cells.\nMajority of ATRX KO cells do not exhibit reduction of alpha-globin genes. Are variable length and repeat # of VNTR\ninvolved in regulation of ATRX dependent alpha globin regulation? Does VNTR variable affect R-loop formation, chromatin\naccessibility and PolII loading?\n2. Figures 2 and 3, ATRX KO only affect 53 DEGs, yet it is unclear how it downregulated 56 pathways. The DEGs should be\nlisted, and gene sets correlate with 56 downregulated pathways need to be detailed analyzed and presented.\n3. ATRX deficiency affects R-loops, genome stability and gene transcription in addition to alpha globin genes. Does CX-\n5461 stabilize R-loop in VNTR that is depended on VNTR variable (Figure 4), as ATRX targets tandem repeats and\ninfluences gene expression in a size-dependent manner?\n4. ATRX KO mediated R-loop stabilization is not HBM VNTR specific, and its effect could be indirect and correlative. Do\ndirect targeting and resolving VNTR R-loops (such as CRISPR-dCas9 targeting ATRX or RnaseH1 to VNTR region) rescue\nalpha globin expression and alleviate alpha thalassemia in ATR-X syndrome associated alpha thalassemia patient\nsamples. Such experiments may be out of scope of current manuscript. However, authors should at least discuss its\npotential translation applications in the discussion section."}, "author_response": "We thank the reviewer for their comments and for appreciating our work on the α-globin locus. The\nreferee is correct in saying that the concept of how ATRX may cause human disease is not novel\nand indeed we and others have previously proposed this model. The difference is that here we have\ntested this hypothesis and proven the role of the putative G-rich repeats by deleting them in the\npresence or absence of ATRX.\nBy focussing in depth on the α-globin locus, we have established a mechanistic understanding of\nhow mutations in ATRX may affect gene regulation. To extend this, we also examined the NME4\nlocus, another ATRX target, and observed effects consistent with those at the α-globin locus. In the\nrevised manuscript, we have included a full list of the dysregulated genes affected by ATRX KO and\nfound 45 out of 71 (63.4%) of them contain a GC-rich tandem or low-complexity repeats, suggesting\nthis might be a general regulation rule of ATRX. Although the erythroid models used in this study\nlimit the number of loci we could test, the mechanistic link we identify between ATRX, R-loop\nresolution, DNA damage, and transcriptional regulation is likely to extend to additional ATRX targets\n(as mentioned in lines 228-234), which could be explored in other models. As in numerous past\nstudies, understanding mechanisms using this model locus have always extended to both normal\nand disturbed expression of many other mammalian genes (Higgs and Gibbons. The molecular basis\nof alpha-thalassemia: a model for understanding human molecular genetics. Hematol. Oncol. Clin.\nNorth Am. 2010).\nOur work also goes beyond prior molecular descriptions by directly connecting these mechanisms\nto human disease, providing, to our knowledge, the first demonstration of this pathway’s clinical\nrelevance. We have now made these points more explicit in the revised manuscript (lines 64-65, 71-\n76, 276-281, 407-419).\nWe agree that our work builds upon findings from the previous work and is consistent with other\nreports. Previous studies only examined or indicated an isolated aspect of ATRX function – such as\nG-quadruplexes (PMID 26991472, 25452430, 30808951, 34162889) or R-loops (PMID 28487353,\n35013239), some in artificial in vitro systems, and have not connected these elements into a unified\npathway to demonstrate how these biological processes interact in a physiological context. As\ndiscussed above, our study is distinguished by integrating these mechanisms and providing direct\nexperimental test of the proposed mechanism in vivo. To highlight this, we have revised the\ndiscussion (lines 273-281) to clarify the novelty and significance of our work.\nThank you for this valuable comment. In response, we have performed additional single-cell\nanalyses to ask whether α-globin downregulation and the increased DNA damage markers co-occur\nwithin the same individual cells. These new results are now presented in Fig. 2i and Extended Data\nFig.3g, with further details provided in the responses below.\nWe acknowledge that the stochastic nature of gene expression changes in the absence of ATRX is\nintriguing. We propose that ATRX deficiency exerts cumulative effects on a subset of cells, as\nsupported by our BFU-E colony assays in which only a fraction of colonies displayed gene\ndownregulation, indicating that impairments in this subpopulation accumulate progressively during\nerythroid differentiation. Specifically, we suspect only cells that accumulate unresolved G4s/R-loops\nand replication stress are to be affected. The likelihood of a replication or transcription fork\nencountering these structures during a dynamic process introduces a stochastic element to the effect.\nNotably, ATRX is not the sole factor capable of destabilising G4s and R-loops; other helicases, such\nas FANCJ DNA helicase, RecQ helicases, and DDX5, can also resolve these structures to release\nthe cells from stress. Therefore, the affected subpopulation likely represents cells that lack ATRX to\nresolve G4s and retain G4s that cannot be resolved by other complementary helicases in time. With\nsuccessive rounds of cell division and differentiation, consequences of these unusual structures are\nmore likely to accumulate and impair DNA and chromatin, ultimately suppressing gene expression.\nWe have now added this explanation in our revised Discussion section (line 371-386).\nThank you for highlighting this. We apologise for the previous omission, and we have now moved\nthe panel previously shown as Extended Data Fig. 1j to the main figure (now Fig. 1f). This revised\nfigure more clearly illustrates the expression levels of HBM and HBA in individual BFU-E clones\nrelative to ATRX expression, as suggested.\nThank you for this excellent suggestion. In response, we examined the occurrence of GC-rich\ntandem or low-complexity repeats (using the RepeatMasker track from UCSC) within 2 kb of all\ndysregulated genes identified in ATRX KO cells. Of the 71 dysregulated genes, we found that 45\nhave GC-rich repeats proximal to their promoters or regulatory elements. We also checked ATRX\nChIP-seq data at these loci and found that ATRX binds all these regions. We have now included a\nfull table summarising these in our revised manuscript (new Table 1) and have updated the text\naccordingly (see lines 228-235).\nThank you for raising this important point. We agree that the connections between DNA damage\nand HBM downregulation were not fully delineated.\nTo address this, we have:\n1. Assessed the expression of DNA damage response gene in the affected HBMlow\nsubpopulation (new data in Fig. 2i and Extended Data Fig. 3g)\n2. Directly measured H2Aub expression (new data in Fig. 2h)\nAs RNF168 expression is lowly expressed in our dataset, as shown in Fig. 2c, it was difficult to\nassess its contribution in the affected cells. However, while revisiting this point, we identified another\nDNA damage response gene, UIMC1 (also known as RAP80), which was more abundant and\nsignificantly upregulated in ATRX KO cells as shown below. RAP80 is a ubiquitin-binding protein\nthat recognises ubiquitinated histones at DNA damage sites and facilitates BRCA1 recruitment to\nthe damaged sites, thereby mediating damage signalling and repair (Sobhian et al, Science 2007).\nFurthermore, a recent study identified RAP80 as a modulator to suppresses genomic abnormalities\naround the damaged site in transcription active regions (Yasuhara et al, Cell Reports 2022).\nTo examine its expression in the affected cells by colouring the cells by the expression level of\nUIMC1, we found that the affected HBM-low ATRX KO cells express high levels of UIMC1 (a, new\ndata in Extended Data Fig. 3g), and this has been further supported by violin plot shown in (b, new\ndata in Fig. 2i). This suggests that the affected subpopulation exhibits upregulated DNA damage\nsignalling and enhanced DNA damage response pathway.\nTo check whether ATRX KO cells have global increase in H2A ubiquitination, we performed H2Aub\nimmunofluorescent staining and found that a subset of ATRX KO cells showed elevated H2Aub\nlevels.\nThese new results have been added to the revised manuscript (Fig. 2h), with text updated from line\n168-177. We acknowledge that further work is needed to demonstrate locus-specific H2A\nubiquitination in the affected subpopulation.\nThank you for raising this point. We agree that detecting the location of DNA damage around the\nVNTR at the α-globin locus would significantly strengthen the study. We have tried to address this\nand collaborated with experts in the DNA damage field. However, measuring locus-specific DNA\ndamage is technically challenging, particularly in our model where damage occurs in only a small\nsubset of cells. To pursue this, we collaborated with Dr. André Nussenzweig to apply END-seq, a\nmethod developed in his group to map DNA double-strand breaks (Canela et al, Molecular Cell\n2016), as well as S1-END-seq to detect single-stranded DNA structures (Matos-Rodrigues et al,\nMolecular Cell 2022). Unfortunately, given the subtle nature of the effect in our model, we were\nunable to detect convincing signals at the α-globin locus, as shown below.\nWe also performed gammaH2AX ChIPmentation in our HUDEP models, which suggested a possible\nenrichment around the VNTR region (highlighted in blue below). However, we do not consider these\nresults sufficiently robust and convincing to draw conclusion, likely due to the low frequency of\naffected cells in the population.\nTherefore, to get around with this point, we instead performed a locus-specific CRISPR-guided DNA\ndamage assay to link DNA damage signalling directly to local gene downregulation. Using this\napproach, we observed distance-dependent perturbation of gene expression around the damage\nsite at the α-globin locus (Fig. 4f, unchanged, shown below for reviewer’s reference).\nFinally, in recognition of the importance of direct detection of locus-specific DNA damage, we have\nexplicitly discussed this limitation in the revised Discussion (lines 386-390).\nWe apologise for the oversight, which resulted from a formatting issue during PDF export from\nPowerPoint. This has now been corrected, and we have carefully reviewed all figures to ensure\nconsistency and accuracy in the revised manuscript.\nIt is true that prior studies (including Wong et al, Genome Research 2010, Lovejoy et al, PLoS\nGenetics 2012, and Huh et al, JCI 2012) have demonstrated that ATRX loss leads to DNA damage.\nOur study does not claim novelty in this respect; rather, it seeks to advance the field by\nexperimentally testing the current speculation that ATRX-mediated DNA damage and G4/R-loop is\nthe cause of disordered gene expression using the alpha-globin cluster as a model. Our work stands\nout by integrating these interconnected processes and demonstrating how ATRX coordinates non-\ncanonical genomic structures, genome stability, and transcriptional output. Furthermore, our findings\nprovide, to our knowledge, the first direct evidence connecting these events to pathogenic phenotype\nin a human genetic disorder.\nTo reflect this, we have revised the introduction (lines 64-65, 71-76) and discussion (lines 276-281,\n407-419) to clarify the novelty and significance of our work.\nThank you for this valuable comment. In response, we have now included the full list of dysregulated\ngenes by ATRX KO in Table 1 of the revised manuscript, along with information on their association\nwith GC-rich repeats and ATRX binding. Notably, a closer inspection of the individual gene identities\nrevealed additional evidence supporting upregulation of DNA damage response pathways. Notably,\nwhile revisiting this analysis and addressing parallel reviewer comment, we identified significant\nupregulation of UIMC1 (RAP80) in ATRX KO cells, as shown below. RAP80 is a well-established\nDNA damage response factor that recognises ubiquitinated histones at DNA damage sites and\nrecruits BRCA1 for repair (Sobhian et al, Science 2007).\nWe also examined UIMC1 expression within the HBM-low ATRX KO cells and found a significant\nincrease (shown below, new data in Fig, 2i), suggesting that these affected cells display robust\nactivation of DNA damage signalling pathways.\nWe agree that this is a very important point.\nWe have performed dot blot assay to confirm there is a genome-wide increase of R-loop\naccumulation in ATRX deficient cells (new data in Fig. 4b).\nWe agree that direct detection of DNA damage around the VNTR would significantly strengthen the\nstudy. We have attempted to address this by performing gammaH2AX ChIPmentation in our HUDEP\nmodels, which suggested a possible enrichment around the VNTR region (highlighted in blue below).\nHowever, we do not consider these results sufficiently robust and convincing to draw conclusion,\nlikely due to the mild effect and low frequency of affected cells in the population.\nWe also collaborated with experts in the DNA damage field trying to address this. With Dr. André\nNussenzweig, we applied END-seq, a method developed in his group to map DNA double-strand\nbreaks (Canela et al, Molecular Cell 2016), as well as S1-END-seq to detect single-stranded DNA\nstructures (Matos-Rodrigues et al, Molecular Cell 2022). Unfortunately, we were unable to detect\nconvincing signals, likely due to the mildness and subset-specific nature of the DNA damage in our\nmodel.\nTherefore, to get around with this point, we instead performed a locus-specific CRISPR-guided DNA\ndamage assay to link DNA damage signalling directly to local gene downregulation. Using this\napproach, we observed distance-dependent perturbation of gene expression around the damage\nsite at the α-globin locus (Fig. 4f, unchanged, shown below for reviewer’s reference).\nWe have discussed this limitation in the revised manuscript (lines 386-390).\nThank you for bringing up the relationship between R-loops and DNA damage repair. In our current\nstudy, the experiments shown in the original Fig 4c,d were performed in the VNTR knockout model,\nwhere the region is deleted and it was not possible to assess R-loop formation at the VNTR in\nresponse to induced DNA damage within this system.\nWe agree that this is an important mechanistic question, especially given recent studies reporting\nthat R-loop formation near DNA double-strand breaks could facilitate DNA damage repair (e.g. Ngo\net al, Nature Communications 2021; Girasol et al, PNAS 2023). Some of these findings have been\ndescribed in non-physiological contexts following the use of DNA-damaging agents, and they found\ntranscription at DSBs can promote local R-loop formation, which in turn provides binding platforms\nfor DNA damage response factors.\nGiven the highly GC-rich (96%) nature of the VNTR at the α-globin locus and its active transcription\nunder physiological conditions, we speculate that, in the absence of ATRX, R-loop formation at this\nsite is primarily driven by transcriptional activity and the high GC content, rather than being the\nconsequence of DNA damage. This interpretation is consistent with the previous data from our group\n(Nguyen et al, EMBO Rep 2017), which showed that R-loops formed at G-rich regions are\ntranscription-dependent. We therefore propose that persistent G4 structures and R-loops in this\ncontext cause DNA damage, rather than being secondary to it. Nevertheless, investigating whether\nR-loop accumulation can also be further enhanced by DNA damage at the VNTR, potentially\nsupporting a bidirectional relationship, is an important and interesting future direction. We have\nadded a discussion of this point in the revised manuscript (lines 327-335) but believe that fully\naddressing this mechanistic question is beyond the current study’s scope.\nWe appreciate the reviewer’s point and acknowledge that we do not directly prove its unwinding or\nhelicase activity. We have now revised our title to be ‘ATRX loss couples genomic instability at G-\nrich repeats to dysregulation of gene expression’.\nWe appreciate the emphasis on statistical robustness. All n values presented in the manuscript\nrepresent biological replicates. Each experiment was performed independently at least three times,\nexcept for the colony-forming unit assay using AAVS1 and ATRX KO CD34⁺ cells, where we\nanalysed over 300 single colonies from two independent batches (n = 2 biological repeats). In this\nspecific assay, gene expression was assessed at the level of individual colonies rather than bulk\nmeasurement between genotype groups, which we believe does not bias the conclusions drawn.\nWe have carefully double-checked all statistical analyses in the study and included quantification for\nthe representative data. Appropriate and rigorous statistical tests were applied across all datasets\nwith n ≥ 3, and detailed descriptions of these tests, as well as exact p-values, are now provided in\nthe respective figure legends, as well as in the ‘Statistical analysis’ method section in the revised\nmanuscript.\nThank you for this insightful comment. To address it, we performed RNase H1 overexpression assay\nby transfecting RNase H1-GFP plasmid into ATRX degron cells and analysed gene expression in\nGFP+ cells (n=3). The results (new data in Fig. 4d) show a partial rescue of HBM expression upon\nR-loop degradation. This suggests ATRX modulates R-loops and G4 structures at least partially\nindependently. Given the high GC content (96%) of the VNTR, G4 formation likely occurs\nintrinsically. In ATRX-deficient cells, transcription enhances both R-loop and G4 generation, leading\ncumulatively to chromatin instability and DNA damage. This new data strengthens our mechanistic\nmodel and we have now discussed this point in the discussion (lines 325-335).\nWe appreciate this suggestion and have systematically re-analysed our scRNA-seq dysregulated\ngene list from ATRX KO CD34+ cells for presence of GC-rich repeats and ATRX binding based on\nour ChIP-seq data. Remarkably, 45 out of 71 dysregulated genes contained nearby GC-rich tandem\nor low-complexity repeats bound by ATRX. We now present these data in new Table 1 and have\nexpanded the text to discuss the potential broader applicability of our model beyond the α-globin\nlocus (lines 228-235).\nWe agree this is an important point that needs further investigation. Ideally, this could be addressed\nby isolating the affected subpopulation and profiling their underlying molecular signatures; however,\nthis is not technically feasible at present due to the stochastic nature of the affected cells. Instead,\nwe have leveraged our single-cell RNA-seq dataset to define affected (HBMlow) and unaffected\n(HBMhigh) subpopulations in ATRX KO sample and compare their transcriptional profiles. This\nanalysis, described in Extended Data Fig. 3e (unchanged, shown below for reviewer’s reference),\nwas performed through GSEA to identify pathways distinguishing these two populations. We have\nprovided the full pathway list and corresponding gene sets in a new supplementary table (Extended\nData Table. 1) in the revised manuscript.\nWe appreciate this point regarding alternative or complementary mechanisms of ATRX-mediated α-\nglobin regulation. Indeed, ATRX’s role in macroH2A regulation at the α-globin locus, as described\nby Ratnakumar et al, 2012, represents an important pathway. We attempted to assess this\nmechanism in our model through macroH2A ChIPmentation, but the signal was not conclusive, likely\ndue to the subtle transcriptional effects observed at the bulk population level. In our study, we\nidentified upregulated DNA damage and H2A ubiquitination in ATRX KO cells, which is associated\nwith transcriptional repression. These may be complementary to macroH2A-mediated regulation, as\nmacroH2A has been implicated in DNA damage responses by accumulating at damaged regions\nand promoting local chromatin condensation, as summarised by Oberdoerffer and Miller, Seminars\nin Cell & Developmental Biology, 2023.\nIn response, we have expanded the Discussion (lines 358-369) to explicitly integrate our findings\nwith the existing literature, emphasising that DNA damage-associated chromatin remodelling and\nmacroH2A deposition likely represent parallel and potentially synergistic mechanisms of α-globin\nrepression upon ATRX loss.\nWe agree that multiple factors may influence ATRX binding during differentiation. Although we have\nnot comprehensively dissected these factors in this study, our previous work demonstrated that\ntranscription alone at tandem repeats can drive ATRX binding (Nguyen et al, EMBO Reports 2017).\nTo avoid overinterpretation, we have revised our wording from ‘transcription-dependent’ to ‘co-\ntranscriptionally’ (line 29) and ‘correlated with transcriptional activation’ (line 199) in the revised\nmanuscript. We also refer to the study supporting transcription as a major driver of ATRX recruitment,\nwhile acknowledging the broader regulatory context in which these interactions occur.\nThank you for recognising the logical progression and importance of our study. While individual\nelements such as ATRX-VNTR binding, G4 structure formation, and macroH2A regulation have\nbeen reported, they were studied separately in different contexts. Our work uniquely integrates and\nexpands these mechanisms into a unified pathway that explains how ATRX loss leads to a-\nthalassemia in a physiological context. In addition, as pointed out above, previous reports have\nhypothesised about how the VNTR might underlie this unusual form of alpha thalassaemia. Here we\nhave experimentally tested this and shown that in the absence of the VNTR, the alpha genes are no\nlonger downregulated when ATRX is removed. In addition, if we artificially induce DNA damage at\nthe position of the VNTR this does downregulate alpha globin expression. Specifically, our study\nprovides mechanistic insights into several previously unresolved questions in the field:\n1. Why ATRX germline mutation leads to only a subtle α-thalassemia phenotype in ATR-X\nsyndrome patient,\n2. Why the gene downregulation occurs in a distance-dependent manner, and\n3. Why ATRX mouse models fail to fully recapitulate human α-thalassemia.\nThese aspects could not be explained by earlier studies in isolation. Our contribution thus represents\nthe first integrated in vivo demonstration linking ATRX, VNTRs, R-loops, G4s, DNA damage and\nchromatin dynamics within the context of human disease. We have emphasized this conceptual\nadvance and its implications in the revised introduction (lines 64-65, 71-76) and discussion (lines\n276-281, 407-419).\nThank you for this insightful question. We agree that the length of the VNTR likely plays a key role\nin ATRX-dependent regulation of α-globin expression. As reported previously by our group (Law et\nal, Cell 2010), the degree of α-globin downregulation in ATR-X syndrome patients correlated with\nVNTR size. In the current study, we provide a mechanistic model to explain this observation -\nnamely, that longer VNTRs are more prone to forming R-loops and G4 structures at the locus, which\nin turn can disrupt local chromatin organisation and transcription of nearby genes.\nWe have determined the VNTR length in all donor samples used in this study. However, due to\nvariability in ATRX knockout efficiency across donors and the relatively modest extent of α-globin\ndownregulation, the current dataset does not allow a robust correlation between VNTR length and\ngene repression. We fully agree that establishing isogenic models carrying VNTRs of different\nlengths would be valuable to directly test whether VNTR size affects chromatin accessibility and Pol\nII loading. Unfortunately, due to the VNTR’s extremely high GC content (~96%), precise CRISPR\nediting across this region remains technically challenging. For this reason, we instead generated a\nmodel in which the entire VNTR region was deleted to assess its functional contribution.\nIn support of the importance of repeat length, an earlier study from our group (Nguyen et al, EMBO\nReports 2017) demonstrated that ATRX recruitment to G-rich tandem repeats depends on repeat\nnumber, orientation, and transcriptional activity. The transcribed repeats form R-loops whose\nabundance correlates with ATRX binding. In the present work, we show that similar R-loop-\ndependent mechanisms occur at the α-globin VNTR, leading to local DNA damage and\ntranscriptional repression.\nThe observation that α-globin downregulation occurs only in a subset of ATRX KO cells likely reflects\nstochastic effects of ATRX loss at the single-cell level. At present, it is technically infeasible to assess\nVNTR length heterogeneity within individual cells to determine whether the affected subset carries\nlonger repeats during differentiation. We have tried to determine the VNTR length in the affected\nBFU-E colonies, however the DNA generated via whole genome amplification from a single colony\ndoes not yield good enough quality for such detection. We recognise this as an important direction\nfor future investigation and have expanded our discussion to highlight this point (lines 291-296, 390-\n394).\nWe appreciate the suggestion to clarify the connection between DEGs and pathway analysis.\nAccordingly, we have included the full list of 53 DEGs in the new Table 1, along with details on their\nassociation with GC-rich repeats and ATRX binding. The 56 dysregulated pathways were identified\nthrough GSEA analysis comparing HBMhigh and HBMlow populations, where the number of DEGs is\nsubstantially larger. This analysis aimed to capture the pathways differentially regulated between\nthe unaffected and affected subpopulations, with strategies outlined in Extended Data Fig. 3e\n(unchanged, shown below for reviewer’s reference).\nin our inducible ATRX degron model and observed a partial rescue of HBM expression (new data in\nFig. 4d). This result supports the idea that R-loop accumulation contributes functionally to α-globin\nrepression upon ATRX loss. As ATR-X syndrome cases are very rare, we have little access to\npatient-derived samples.\nWe thank the reviewer for their positive feedback. In response to the suggestion about the title,\nwe have revised it to more accurately reflect the scope of our work: “ATRX loss couples\ngenome instability at a G-rich repeat to dysregulation of human alpha-globin expression”.\nWe appreciate the importance of clarifying the system used. In our initial terminology, “in vivo”\nreferred to live cells in their native chromatin context (distinct from reconstituted systems),\nwhich is conventionally used in a specific field of chromatin biology. However, to prevent any\nconfusion for a broader readership, we have removed the term “in vivo” throughout the\nmanuscript and clarify that our findings were obtained from human cell culture models.\nWe appreciate the reviewer’s suggestion to use living organisms such as ATR-X patient\nsamples. However, there is currently no suitable in vivo system that could provide additional\nmechanistic insight beyond what we have shown in this study.\nAs noted in the manuscript, the mouse α-globin cluster lacks the G-rich VNTR that underlies\nthe ATRX-associated phenotype in humans. Indeed, mutations of ATRX in the mouse, do not\ncause alpha thalassaemia (Tillotson et al. Hum Mol Genet 2023) and we have the\nhaematological data from a mouse model of ATRX (Tillotson et al. unpublished) showing\nnormal readout of red blood cell parameters which we could include in the current manuscript\nif required. Therefore, mouse models cannot reproduce this aspect of the disease.\nRegarding ATR-X patient samples, ATR-X syndrome is exceptionally rare – with only ~200\nreported cases worldwide. Acquisition of adequate patient material is therefore unfortunately\nimpractical. Of note, we have previously analysed two affected brothers and published the\ncellular heterogeneity in their erythroid cells (Truch J et al. Nat Commun 2022). Given the\nscarcity of patient samples, in the current study we established a physiologically relevant\nmodel using primary CD34+ cells from healthy donors, which faithfully recapitulates the key\nmolecular and phenotypic features of the disease.\nIn addition, to understand the underlying molecular mechanisms to explain the observations\nin patients, we established and employed a HUDEP-2 degron cell model to perform two key\nexperiments that directly establish pathogenic relevance: 1. Deletion of the VNTR abolishes\nthe ATRX-loss phenotype. 2. Targeted induction of DNA double strand break at this site,\nremote from the alpha genes, reinstates the phenotype in a pattern identical to that seen when\nATRX is mutated. These demonstrate experimentally for the first time that the G-rich VNTR\nitself is causally linked to the disease mechanism. Such gene-editing experiments are not\nfeasible or ethically permissible in humans in vivo.\nWe appreciate the reviewer’s feedback on these points and the opportunity to clarify this. In\nthe revised manuscript, we have revised the wording to make sure that the novelty and broad\napplicability are appropriately stated (lines 34, 303-305, 416-418).\nWhile we acknowledge that previous studies have individually associated ATRX with certain\naspects of G4, R-loops, or replication stress, none have, to our knowledge, experimentally\nconnected them and demonstrated an integrated causal mechanism linking these features to\na disease phenotype. Our study provides a direct experimental validation of this model at the\nhuman α-globin locus. This extends prior hypotheses into experimentally proven causality. We\nhave explicitly noted this significance in the Discussion (lines 270-280).\nTo our knowledge, this mechanism of dysregulation of gene expression mediated by a long-\nrange VNTR in a human genetic disease context is novel. To make this specific point clearer,\nwe have clarified it in the revised Abstract and Discussion (lines 34, 416-418). We would like\nto emphasise that a very high proportion of the principles underlying normal gene regulation\nand how this is perturbed in human genetic disease were first discovered at the globin gene\nloci and subsequently found to be generally true, including the original identification of ATRX\ngene itself (Gibbons, Picketts et al. Cell 1995).\nWe thank the reviewer for these comments. We recognise that the working model is not yet\nfully delineated and that additional studies will be required for a complete mechanistic picture,\nas discussed as future avenues in the manuscript. Nevertheless, we believe the current data\nprovide clear mechanistic insights into several previously unexplained observations,\nsupported by direct experimental evidence:\n1. Why do ATR-X syndrome patients present only a subtle α-thalassemia phenotype?\nOur scRNA-seq analysis demonstrates that α-globin downregulation occurs only in a\nsubset of ATRX-deficient cells, rather than as a uniformly mild reduction across all cells.\nThis conclusion aligns very well with findings in patient-derived cells (Truch et al, Nat\nCommun 2022).\n2. Why the gene downregulation occurs in a distance-dependent manner?\nWe show that gene dysregulation depends on the VNTR and on secondary R-loop\nformation and DNA damage, which together account for why genes located closer to\nthe VNTR are more strongly affected.\nImportantly, two key experiments, the VNTR deletion and targeted DNA damage induction at\nthe α-globin cluster, directly test causality and substantiate the proposed model. These\nfindings establish a direct link between ATRX loss, VNTR instability, and downstream\ntranscriptional consequences.\nRegarding the broader mechanistic explanation of phenotypic heterogeneity, we agree that\nmultiple factors could contribute. However, differentiation heterogeneity appears unlikely to be\na major driver: BFU-E colony assays show comparable morphology and colony numbers\nbetween ATRX-null and control cells (Extended Data Fig. 1h-i), indicating that the\ndifferentiation is not significantly perturbed. We have emphasised this point in the revised\nmanuscript (line 375). Instead, our data suggest heterogeneity arises from molecular events\nat the G-rich VNTR. As discussed in the manuscript (lines 371-386), only cells that accumulate\nunresolved G4 /R-loops and replication stress exhibit transcriptional defects. The probability\nof replication or transcription forks encountering these structures introduces a stochastic\nelement, potentially also modulated by other helicases in addition to ATRX. We agree this is\nan important direction for future research, however, the inherently stochastic nature of the\nprocess presents technical challenges for obtaining locus-specific evidence using current\nmodels. As noted as a limitation and future direction in the Discussion (lines 387-390), a more\nrobust model with a stronger and more consistent phenotype will likely be required to address\nthese questions definitively.\nWe appreciate this feedback and have revised the title to better reflect the study’s focus. The\nnew title, “ATRX loss couples genome instability at a G-rich repeat to dysregulation of human\nalpha-globin expression” more accurately captures the scope of the work.\nWe also thank the reviewer for recognising the ‘functional and mechanistic evidence at this\nsingle, disease-relevant VNTR’ at the α-globin locus. As mentioned above, this locus has long\nserved as a foundational model for understanding gene regulation, and our study provides a\nmechanistic framework at this site that may guide future investigations into whether similar\nprinciples apply elsewhere in the genome."}, {"round": 2, "reviewer_comments": {"reviewer_1": "In the absence of being able to directly assess DNA damage at the VNTR, the authors have adequately addressed my other concerns. Perhaps there is a better title than the one currently provided, as the authors cannot conclusively show that there is genomic instability at the G-rich repeats. Beyond that, I have no further comments, and the authors should be congratulated on their well-performed study and nuanced interpretation of their data.", "reviewer_2": "All concerns have been addressed.", "reviewer_3": "1) The authors should clearly discuss the constraints of their model system. Contrary to statements from the authors, the study lacks in vivo data. All mechanistic findings rely on in vitro models (primary human CD34+ cells and HUDEP-2 cell lines) and do not constitute true in vivo analyses i.e., experiments performed in a living organism and cannot assess physiological and disease states. The authors should clarify in the abstract and discussion that findings were made in human cell culture models to eliminate misinterpretation about the nature of the expermental evidence.\n2) Only gene-edited lines from healthy donors were used. Use of cells from ATR-X patients would bolster disease relevance.\n3) The manuscript repeatedly overstates the novelty and clinical relevance of their findings. i.e. \"uncovers a new molecular mechanism of human genetic disease\" and \"reveals an entirely new pathogenic mechanism underlying human genetic disease” and “disruption of this pathway to maintain genome integrity may underlie not only the developmental defects observed in ATR-X syndrome but also contribute to the role of ATRX mutations in ageing and cancer\". The conclusion that this is a broadly applicable \"entirely new\" pathogenic mechanism is inappropriate given the focus on a single locus and in vitro cell systems. References to the finding as \"an integrated model that unifies these mechanistic elements\" may overstate the originality, since several cited studies have previously connected ATRX loss to G4 formation, R-loops, replication stress, and DNA damage signaling. The principal novelty here appears to be experimental demonstration at the alpha-globin VNTR with supporting cellular data but not a discovery of the general paradigm itself.\n4) The authors state that their findings account for \"several previously unexplained observations in ATR-X syndrome,\" including phenotypic heterogeneity and the subset nature of the affected cells. While the study offers support, the data are mainly correlative, and broader mechanistic explanations involving differentiation heterogeneity or additional modifying factors are not excluded. Overall, the study does not fully clarify what drives heterogeneity, nor does it provide definitive single-cell or clonal evidence for the underlying stochastic events triggering DNA damage in only a subset of ATRX-null cells. Requested revisions are discussed as avenues for future research. While the discussion attempts to bridge the gaps, much of this interpretation remains speculative and is not directly substantiated by the presented data.\n5) The title’s use of the plural \"G-rich repeats\" and generalization to \"gene expression\" may suggest a more global effect than was directly shown. Most functional and mechanistic evidence is at this single, disease-relevant VNTR, and while genome-wide correlations are discussed, only limited data are provided from other loci.", "reviewer_4": "The Authors have answered all concerns that I raised. The current revision including additional experiments preformed significantly improves the manuscript and supports the key findings that ATRX regulates a-globin gene by preventing persistent R-loop formation. I have not further questions."}, "author_response": "We thank the reviewer for their positive feedback. In response to the suggestion about the title,\nwe have revised it to more accurately reflect the scope of our work: “ATRX loss couples\ngenome instability at a G-rich repeat to dysregulation of human alpha-globin expression”."}]

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