m6A and the NEXT complex direct Xist RNA turnover and X-inactivation dynamics

Wei, Guifeng; Coker, Heather; Rodermund, Lisa; Almeida, Mafalda; Roach, Holly L.; Nesterova, Tatyana B.; Brockdorff, Neil

doi:10.1038/s41594-025-01663-w

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Published: 09 September 2025

m⁶A and the NEXT complex direct Xist RNA turnover and X-inactivation dynamics

Nature Structural & Molecular Biology (2025)Cite this article

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Abstract

X-chromosome inactivation (XCI) in mammals is orchestrated by the noncoding RNA X-inactive-specific transcript (Xist) that, together with specific interacting proteins, functions in cis to silence an entire X chromosome. Defined sites on Xist RNA carry the N⁶-methyladenosine (m⁶A) modification and perturbation of the m⁶A writer complex has been found to abrogate Xist-mediated gene silencing. However, the relative contribution of m⁶A and its mechanism of action remain unclear. Here we investigate the role of m⁶A in XCI by applying rapid degron-mediated depletion of METTL3, the catalytic subunit of the m⁶A writer complex, an approach that minimizes indirect effects because of transcriptome-wide depletion of m⁶A. We find that acute loss of METTL3 and m⁶A accelerates Xist-mediated gene silencing and this correlates with increased levels and stability of Xist transcripts. We show that Xist RNA turnover is mediated by the nuclear exosome targeting complex but is independent of the principal nuclear m⁶A reader protein YTHDC1. Our findings demonstrate that the primary function of m⁶A on Xist RNA is to promote Xist RNA turnover, which in turn regulates XCI dynamics.

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Main

X-chromosome inactivation (XCI) is a developmentally regulated process that evolved in mammals to equalize the levels of X-linked gene expression in XX females relative to XY males¹. Silencing of a single X chromosome in cells of XX embryos is orchestrated by the X-inactive-specific transcript (Xist), a ~17-kb noncoding RNA, which accumulates in cis across the future inactive X (Xi) chromosome^2,3,4,5. Functional elements within Xist RNA have been assigned in large part to tandem repeat blocks labeled A–F that are distributed across the length of the transcript. Most notably, the 5′-end-located A-repeat element has been found to be critical for Xist-mediated gene silencing⁶. Identification of RNA-binding proteins (RBPs) that interact with the A-repeat and other elements has been achieved using both proteomic^7,8,9 and functional genetic screening^10,11 strategies. These approaches led to the identification of the RBP SPEN as a critical factor for Xist-mediated silencing, functioning by binding to Xist A-repeat region¹² and recruitment of the NCoR–HDAC3 histone deacetylase complex^7,13. The Polycomb system, which contributes to Xi silencing, is recruited by the RBP hnRNPK, which binds to the Xist B/C-repeat region^14,15. Another RBP, the SPEN-related protein RBM15, was identified using both proteomic and functional screening^8,10. Follow-up studies have shown that RBM15 is an accessory subunit of the multiprotein complex that catalyzes RNA N⁶-methyladenosine (m⁶A)¹⁶. Other subunits of the m⁶A writer complex, particularly WTAP, were also identified in the Xist proteomic and functional screening experiments^8,10. Notably, the recruitment of both RBM15 and WTAP to Xist depends on the Xist A-repeat region⁸.

Building on initial observations implicating the m⁶A writer complex in XCI, it was reported that RBM15 directs m⁶A activity to two sites immediately downstream of the Xist A-repeat and E-repeat regions and perturbation of the complex, or of the protein YTHDC1, which binds to m⁶A-modified RNA in the nucleus, strongly abrogates Xist-mediated gene silencing¹⁶. In contrast, other studies that analyzed Xist-mediated gene silencing reported minor or negligible effects on XCI following knockout of genes encoding subunits of the m⁶A writer complex¹⁷ or following deletion of m⁶A sites in the vicinity of the Xist A-repeat^17,18. Likely explanations for these discrepancies include the use of different cell models, different assays to assess Xist-mediated silencing and different strategies for perturbation of the m⁶A writer complex¹⁹. Of particular note is that m⁶A impacts the function of several thousand mRNAs such that chronic or long-term gene knockout studies have the potential to lead to notable secondary or indirect effects.

In this study, we exploit an alternative approach, acute protein depletion with the dTAG degron system²⁰, to investigate the role of the m⁶A writer complex in Xist-mediated silencing. Our study demonstrates that the primary function of m⁶A on Xist RNA is to promote transcript turnover and that removal of METTL3 increases the rate of Xist-mediated silencing. Additionally, we find that the nuclear exosome targeting (NEXT) complex is essential for Xist degradation through a pathway that functions independently of the major nuclear m⁶A reader protein YTHDC1.

Results

Acute METTL3 depletion accelerates Xist-mediated gene silencing

In recent work, we analyzed the role of m⁶A in regulating nascent RNA processing, making use of the dTAG degron system²¹ to rapidly deplete METTL3, the catalytic subunit of the m⁶A writer complex, in iXist-ChrX_Cast (clone C7H8) mouse embryonic stem cells (mES cells)¹⁷. We used MeRIP-seq (m⁶A RNA immunoprecipitation and sequencing) to show that acute depletion of METTL3 for 2 h, followed by 24 h of Xist induction with continued METTL3 depletion, results in a rapid transcriptome-wide loss of m⁶A, including at major peaks in proximity to the A-repeat (exon 1) and E-repeat (exon 7) of Xist²¹. To further verify this finding, we performed an extended METTL3 depletion (24 h) before Xist induction (Extended Data Fig. 1a). Both conditions result in a near complete loss of the majority of m⁶A peaks across the transcriptome, including those on Xist (Extended Data Fig. 1b–e).

Here, we used the same degron strategy to investigate how acute loss of METTL3 and m⁶A affects Xist-mediated chromosome silencing. iXist-ChrX_Cast mES cells have an interspecific Mus castaneus × 129 strain background with a stable XX karyotype and are engineered with a TetOn promoter for induction of Xist expression specifically from the Mus castaneus X chromosome¹⁷. Accordingly, we are able to isolate chromatin-associated RNA and subject it to sequencing (ChrRNA-seq) to accurately determine the relative expression level of active X (Xa) and Xi alleles for a large number of X-linked genes that have informative single-nucleotide polymorphisms (SNPs). In addition to two previously described lines with a METTL3 C-terminal FKBP12^F36V tag²¹, we derived two independent lines with METTL3 tagged with FKBP12^F36V on the N terminus (Fig. 1a) in the iXist-ChrX_Cast background. In all FKBP12^F36V-tagged cell lines METTL3 depletion occurred rapidly, within 2 h of adding the dTAG-13 reagent (Fig. 1b and Extended Data Fig. 2a), and moreover resulted in strongly reduced levels of METTL14, a subunit of the m⁶A complex that heterodimerizes with METTL3 (Fig. 1b and Extended Data Fig. 2b). We noted a reduction in levels of N-terminal FKBP12^F36V–METTL3, indicating that insertion of the tag affects translation or stability of METTL3 protein (Extended Data Fig. 2c).

**Fig. 1: Acute depletion of METTL3 results in accelerated XCI.**

We went on to quantify Xist-mediated silencing following METTL3 depletion as outlined in Fig. 1c. We analyzed silencing at an early time point, after 24 h Xist induction (with or without prior dTAG-13 treatment for 2 h), to minimize potential indirect effects of m⁶A depletion (Xist-mediated silencing in the iXist-ChrX_Cast mES cells occurs progressively over a period of around 6 days²²). The results are summarized in Fig. 1d. In the absence of dTAG-13 reagent, silencing levels in FKBP12^F36V-tagged lines were very similar to those seen in control (C7H8) cells, indicating that there are no effects attributable to addition of the degron at the C or N terminus of METTL3. Interestingly, addition of dTAG-13 resulted in a highly reproducible enhancement or acceleration of Xist-mediated silencing, evident in all four independently derived clones (Fig. 1d and Extended Data Fig. 1f). Of note, accelerated silencing is the converse of the silencing deficiency reported in prior work using constitutive knockout or knockdown of METTL3 and other subunits of the m⁶A writer complex^16,17. This difference likely reflects that acute METTL3 depletion is less influenced by indirect effects compared to chronic knockout experiments. Indeed, global gene expression differences in our study correlate better with m⁶A-modified mRNAs compared to published studies that used long-term knockout approaches²³ (Extended Data Fig. 2d). Principal component analysis (PCA) comparing silencing in untreated cells with acute depletion of METTL3 after 24 h of Xist induction (Fig. 1e), together with silencing analysis for previously defined gene categories^15,17,22 (Extended Data Fig. 2e–h), indicated that all X-linked genes are equally affected by accelerated silencing.

To determine whether the observed acceleration of Xist-mediated silencing is attributable to loss of METTL3 catalytic function, we performed complementation experiments using ectopic expression of GFP–METTL3 transgenes. Transgene constructs were integrated under the control of the Rosa26 constitutive promoter into the H5 clone with C-terminal degron-tagged METTL3 using CRISPR–Cas9-facilitated homologous recombination. In parallel, we established lines using a transgene encoding GFP–METTL3-D395A, a substitution that ablates METTL3 catalytic activity²⁴. Constitutive expression of GFP–METTL3 transgenes was maintained in both the presence and the absence of dTAG-13 (Extended Data Fig. 3a–c).

Both transgene encoded proteins reversed the observed reduction in METTL14 protein levels (Extended Data Fig. 3b,c versus Fig. 1b and Extended Data Fig. 2b), indicating the formation of stable GFP–METTL3/METTL14 heterodimers. Compared to wild-type (WT) GFP–METTL3, levels of GFP–METTL3-D395A were reduced (Extended Data Figs. 2c and 3b,c). This effect was not seen in the presence of dTAG-13 and is not linked to transcriptional levels (Extended Data Fig. 3b–d). A possible explanation is that METTL3-dependent m⁶A autoregulates the complementary DNA-derived ectopic METTL3 transcript through RNA degradation. We went on to analyze Xist-mediated silencing in the transgene complementation lines. ChrRNA-seq analysis showed that ectopic expression of WT GFP–METTL3 fully complements the accelerated silencing phenotype observed following dTAG-13 treatment, whereas expression of GFP–METTL3-D395A has no effect (Fig. 1f and Extended Data Fig. 3e).

To confirm that accelerated Xi gene silencing is attributable to METTL3 catalytic activity, we made use of a recently developed pharmacological METTL3 inhibitor, STM2457 (ref. ²⁵). STM2457 treatment of parental C7H8 XX mES cells resulted in changed levels of YTHDC1 and WTAP and altered ratios of alternative splicing (Extended Data Fig. 4a,b), as occurs following acute depletion of METTL3 (ref. ²¹). We then analyzed Xi gene silencing following treatment of cells with either DMSO or STM2457 for 6 h, followed by 24 h of Xist induction under continued treatment (Extended Data Fig. 4c). ChrRNA-seq analysis revealed that low-dose STM2457 treatment results in a modest increase in Xist RNA levels and accelerated XCI dynamics, with higher doses eliciting a clearly enhanced effect (Extended Data Fig. 4d,e). Collectively, these results confirm the role of METTL3 in regulating the rate of Xist-mediated silencing and further support that METTL3 function in this scenario is through m⁶A catalysis.

Accelerated XCI is linked to increased levels and stability of Xist RNA

We noted a close correlation between accelerated Xist-mediated silencing and levels of Xist RNA, as determined from ChrRNA-seq datasets. Specifically, increased Xist RNA levels up to approximately twofold were apparent following acute METTL3 depletion in the independent N-terminally and C-terminally tagged cell lines (Fig. 2a and Extended Data Fig. 1f). Additionally, complementation with WT GFP–METTL3 but not GFP–METTL3-D395A restored Xist RNA levels to those seen in untreated cells (Fig. 2b and Extended Data Fig. 3f).

**Fig. 2: Xist RNA levels are elevated following acute depletion of METTL3.**

To further investigate the effect of acute METTL3 depletion on Xist RNA, we used super-resolution three-dimensional structured illumination microscopy (3D-SIM) imaging to assay features of Xist RNA domains at the single-cell level. For these experiments, we engineered the METTL3 C-terminal degron into previously described iXist-ChrX₁₂₉ XX mES cells in which the TetOn-inducible Xist allele has a Bgl stem-loop array integrated into Xist exon 7, allowing detection of Xist RNA molecules through binding of a BglG–HaloTag fusion protein labeled with fluorescent Halo dyes²⁶ (Fig. 2c and Extended Data Fig. 2a). In prior work using this system, we reported that Xist RNA accumulates to maximal levels of around 50–100 molecules per cell over a period of 1.5–5 h, referred to as the expansion phase. A time point of 24 h was previously selected where Xist RNA levels have attained a steady state. Using these parameters, we observed an increase in the number of Xist molecules following acute METTL3 depletion (Fig. 2d,f), in agreement with the ChrRNA-seq data. In addition, the volume encompassing Xist centroids (overall Xist domain size) was also significantly increased at 1.5 h (expansion phase) and 24 h (steady-state phase) of Xist induction (Fig. 2e,f). These observations confirm that acute depletion of METTL3 and m⁶A leads to increased Xist RNA levels and an enlarged Xist domains corresponding to the Xi territory.

We also investigated whether other well-characterized nuclear long noncoding RNAs (lncRNAs) that are m⁶A modified are similarly affected by acute METTL3 depletion. Accordingly we examined levels of Neat1, Malat1 and Kcnq1ot1 RNAs, all of which are expressed in mES cells and have high levels of METTL3-dependent m⁶A (Extended Data Fig. 5a–c). Levels of Neat1 and Malat1 were unaffected by acute METTL3 depletion; however, similarly to Xist RNA, Kcnq1ot1 levels increased approximately 1.5–2-fold (Extended Data Fig. 5d–f). The effect on Kcnq1ot1 levels was dependent on METTL3 catalytic activity (Extended Data Fig. 5f, right).

Increased abundance of Xist RNA following acute depletion of METTL3 could result from changes in the rate of Xist RNA transcription and/or RNA turnover. To investigate these possibilities, we applied RNA-SPLIT (sequential pulse localization imaging over time) coupled to super-resolution 3D-SIM microscopy²⁶ to differentially label successive waves of Xist transcripts (presynthesized and newly synthesized) before fixation. The labeling regimen for determining turnover rates is shown in Fig. 3a. Experiments were performed at both the expansion phase and the steady-state phase using a 20-min interval. A 2-h dTAG-13 treatment was performed before Xist induction to minimize secondary or indirect effects. Example images in Fig. 3b are from the expansion phase. As shown previously, turnover of Xist RNA occurs within 140 min at the expansion phase and 220 min at the steady-state phase²⁶ (Fig. 3b,c). In marked contrast, following acute METTL3 depletion, there was little Xist RNA turnover detectable across the entire time course of the experiment (220 min) during both the expansion and the steady-state phases (Fig. 3b,c and Supplementary Fig. 1). Reduced turnover of Xist transcripts was also demonstrated using an orthogonal approach, SLAM-seq²⁷, based on transient 4sU labeling of newly synthesized RNA (Extended Data Fig. 6a–c). Allele-specific analysis using these sequencing data confirmed accelerated silencing and increased Xist RNA levels following acute METTL3 depletion (Extended Data Fig. 7).

**Fig. 3: Acute depletion of METTL3 stabilizes Xist RNA.**

We further applied RNA-SPLIT to measure Xist transcription rates in the presence and absence of m⁶A, achieved by quantifying foci for newly synthesized Xist RNA over time during expansion phase. As shown in Fig. 3d,e, there is a significantly reduced transcription rate in the acute METTL3 depletion condition compared to WT cells. This finding is consistent with prior work demonstrating a feedback mechanism that links Xist transcription and turnover²⁶. Accordingly, we conclude that loss of m⁶A results in accelerated X-chromosome silencing because of overaccumulation of Xist transcripts.

Xist RNA turnover is mediated by the ZCCHC8–NEXT complex independently of YTHDC1

The cellular functions of m⁶A are mediated by reader proteins that can bridge to downstream pathways. YTHDC1 is the best-characterized protein that directly recognizes m⁶A in the nucleus²⁸. Interestingly, YTHDC1 coimmunoprecipitation experiments revealed an association with ZCCHC8, a core subunit of the NEXT complex that targets nonpolyadenylated transcripts in the nucleus for degradation²⁹. Both YTHDC1 and ZCCHC8 have a role in degrading nonpolyadenylated chromatin-associated regulatory RNAs (carRNAs), for example, PROMPTs and eRNAs^30,31. Consistent with this finding, ZCCHC8 has been reported to interact with YTHDC1 in experiments using stable isotope labeling in cell culture and mass spectrometry²⁹. The YTHDC1–RNA exosome axis has also been implicated in the degradation of other nuclear RNAs, for example, SμGLT lncRNA³² and C9ORF72 repeat RNA³³.

To investigate whether YTHDC1 is important for regulating Xist RNA turnover, we used CRISPR–Cas9 facilitated genome editing to establish XX mES cell-derived lines with the FKBP12^F36V degron tag inserted into the gene encoding YTHDC1 (Fig. 4a). YTHDC1 depletion on addition of dTAG-13 reagent was validated by western blot analysis (Fig. 4b,c) and examination of the effects on Tor1aip2 alternative last exon splicing, which is significantly affected by METTL3 and m⁶A and conditional YTHDC1 knockout²¹ (Extended Data Fig. 8a,b). We went on to assay Xist-mediated silencing and Xist RNA levels following YTHDC1 depletion as described above. We observed no increase in the silencing rate or in the levels of Xist RNA in two independent degron-tagged cell lines (Fig. 4d,e and Extended Data Fig. 8c,d). If anything, both Xist RNA levels and the silencing efficiency of X-linked genes appeared modestly reduced compared to controls. However, this reduction was notably less pronounced than that observed with acute depletion of known XCI regulators, for example PCGF3/5 (ref. ²²) (Fig. 4d). Additionally, there was little or no effect on Xist RNA stability by acute depletion of YTHDC1, as determined by SLAM-seq (Extended Data Fig. 6c). Similarly, Kcnq1ot1 RNA, levels of which increase following METTL3 depletion, were unaffected by YTHDC1 depletion (Extended Data Fig. 5g–i, left).

**Fig. 4: Xist RNA turnover is independent of the m⁶A nuclear reader protein YTHDC1.**

We went on to investigate the role of the NEXT complex in Xist RNA turnover by inserting the FKBP12^F36V degron tag into the gene encoding the core subunit ZCCHC8 in XX mES cells (Fig. 5a and Extended Data Fig. 9a,b). As an additional control, we established XX mES cell lines with the FKBP12^F36V degron tag inserted into the gene encoding ZFC3H1, an essential subunit of the poly(A) tail exosome targeting (PAXT) complex³⁴ (Fig. 5b and Extended Data Fig. 9a,c). PAXT mediates an alternate pathway for degradation of polyadenylated RNA in the nucleus, potentially functioning as a timer to remove aberrant RNAs that are not efficiently exported³⁴. dTAG-13 treatment led to rapid and complete depletion of the FKBP12^F36V-tagged proteins within 2 h (Fig. 5a,b). We noted that m⁶A-dependent alternative last exon splicing of the Tor1aip2 gene was not affected by acute depletion of ZCCHC8 or ZFC3H1, indicating that neither NEXT nor PAXT is required for m⁶A deposition on target mRNAs (Extended Data Fig. 9d,e). Acute ZCCHC8 depletion was further validated by monitoring upregulation of PROMPTs (Extended Data Fig. 10a,b).

**Fig. 5: The NEXT complex mediates Xist RNA turnover in the cell nucleus.**

We went on to perform ChrRNA-seq to assay Xist-mediated silencing after 24 h of Xist induction, in either the presence or the absence of NEXT or PAXT complexes using the approach described above for analysis of METTL3 and YTHDC1. As shown in Fig. 5c, acute depletion of ZCCHC8 resulted in strongly accelerated silencing, whereas depletion of ZFC3H1 resulted in a marginal reduction in gene silencing (Fig. 5d). Consistent with these observations, Xist RNA levels were elevated following depletion of ZCCHC8 but not of ZFC3H1, where Xist levels were slightly lower if anything (consistent with marginally reduced gene silencing) (Fig. 5e,f). The higher Xist RNA levels and stability following acute ZCCHC8 depletion are correlated with an even more marked acceleration of silencing than that was seen with acute METTL3 depletion (Fig. 1d versus Fig. 5c). Upregulation of Xist RNA upon acute depletion of ZCCHC8 and NEXT is evident across the entire transcript (Extended Data Fig. 10c). PCA indicates that accelerated silencing affects X-linked genes equivalently across the X chromosome, which contrasts with the silencing deficiency observed upon knockout of the key silencing factor SPEN or deletion of B/C-repeats in Xist (Extended Data Fig. 10d). Levels of Kcnq1ot1 RNA were similarly elevated following acute depletion of ZCCHC8 but not ZFC3H1 (Extended Data Fig. 5g–i, right). SLAM-seq analysis indicates that elevated Xist RNA levels following acute ZCCHC8 depletion are attributable to increased transcript stability (Extended Data Fig. 6c). Taken together these results suggest that m⁶A promotes Xist RNA turnover by the NEXT complex independently of YTHDC1.

Discussion

The acceleration of Xist-mediated silencing that we observe following acute METTL3 depletion conflicts with prior studies that used long-term knockout or knockdown strategies and reported abrogation of silencing to a greater or lesser degree^16,17. Differences observed in our experiments are likely attributable to reduced indirect effects from acute as opposed to chronic depletion of METTL3. This conclusion is supported by the observation that global mRNA expression changes show an improved correlation with m⁶A target mRNAs with acute METTL3 depletion compared to chronic knockout or knockdown. Although we cannot pinpoint with certainty why perturbation of the m⁶A pathway in prior studies resulted in abrogated Xist-mediated silencing, a possible explanation could lie in changed levels of mRNAs encoding proteins that regulate expression of key silencing factors. Indeed, mRNAs encoding the silencing factors SPEN, HDAC3 and HNRNPU are all m⁶A modified. Regardless, our findings underscore that caution needs to be exercised in interpreting experiments involving chronic perturbation of the m⁶A pathway because of its roles in regulating transcription and RNA metabolism at a global level^35,36. Intriguingly, the Xist A-repeat region is bound by RBPs such as SPEN, which promotes Xist RNA stability, and RBM15 and WTAP, which contribute to its destabilization through m⁶A modification. The opposing effects of these pathways on Xist RNA stability highlight a regulatory balance that warrants further investigation.

Our previous work reported that deletion of the m⁶A region in Xist exon 1 has minimal effects on Xist RNA levels and XCI dynamics^17,18. In this study, we generated a deletion of the m⁶A region within Xist exon 7, either alone or in combination with deletion of the exon 1 m⁶A region, to further investigate the functional contribution of distinct m⁶A regions to Xist RNA regulation. Unexpectedly, deletion of the exon 7 m⁶A region resulted in impaired gene silencing and a marked reduction in Xist RNA levels (Supplementary Fig. 2). Given that the deletion is located far from the Xist promoter, we speculate that the observed reduction in RNA levels is likely because of decreased transcript stability. Notably, the double-deletion line displayed a similar phenotype to the exon 7 m⁶A region single deletion, with no evidence of additive effects (Supplementary Fig. 2). These findings can be interpreted in several ways. The exon 7 m⁶A region may overlap with an important RNA stability element, the activity of which is inhibited by m⁶A deposition. Alternatively, the deletion may impair the activity of a neighboring functional element, such as the Xist E-repeat, which is known to influence Xist RNA localization, or may alter the splicing pattern of the transcript. Lastly, the deletion could lead to structural rearrangements in the RNA by juxtaposing sequences that are normally spatially separated, thereby disrupting higher-order folding of Xist RNA and compromising its stability or function. Disentangling the precise roles of individual m⁶A sites within Xist remains a notable challenge and will require further targeted investigation.

Our results indicate that accelerated silencing following acute METTL3 depletion is linked to increased levels of Xist RNA, which in turn result from decreased Xist RNA turnover. This interpretation is supported by the similar phenotype seen following acute depletion of the NEXT subunit ZCCHC8. We envisage that higher Xist RNA levels result in an increased number of molecules accumulating on the X chromosome, thereby amplifying the recruitment of silencing factors that mediate gene silencing in X inactivation. Of note, the increased Xist RNA levels linked to reduced turnover are tempered by a reduction of Xist transcription rates, consistent with our prior analyses indicating feedback control between Xist transcription and stability²⁶. The basis for feedback control between Xist transcription and turnover remains unknown and is an important topic for future studies.

The finding that NEXT but not PAXT regulates Xist RNA turnover is perhaps unexpected given that Xist is polyadenylated and NEXT has been linked to regulating nonpolyadenylated nuclear RNAs such as PROMPTs and eRNAs³⁷. One possible explanation is that the poly(A) tail of Xist molecules localized along the Xi chromosome is protected from NEXT activity, for example, by poly(A)-binding proteins such as PABPN1 or by a folded back structure similar to the lncRNA MALAT1 (ref. ³⁸). Progressive erosion of this protection over time would, thus, initiate NEXT–exosome complex engagement to trigger degradation from the 3′ end. Consistent with this idea, our previous RNA-SPLIT analysis demonstrates that Xist molecules in WT cells remain relatively stable for an extended period of around 90 min before showing rapid exponential degradation kinetics²⁶.

The marked increase in Xist RNA stability, Xist RNA levels and Xi silencing rate observed with both METTL3 and ZCCHC8 depletion, suggests that m⁶A and the NEXT complex function together to regulate Xist RNA turnover. On the basis of prior studies identifying the YTHDC1–NEXT axis and its role in regulating carRNAs, we anticipated that YTHDC1 could bridge Xist RNA with NEXT for m⁶A-mediated control of turnover. However, given that acute YTHDC1 depletion has little to no notable effect on Xist RNA turnover, we speculate that there is an alternative pathway that links m⁶A to the NEXT complex. In support of this idea, we observe no effect of YTHDC1 depletion on levels of the lncRNA Kcnq1ot1 (Extended Data Fig. 5i), which, like Xist, is chromatin associated and functions to silence genes in cis³⁹. We envisage two possible models, a direct pathway whereby an unidentified reader protein interacts with both m⁶A and NEXT or an indirect pathway where m⁶A enhances the association of Xist RBPs that consequently promote NEXT–exosome complex access and activity on Xist (Fig. 5g). In relation to the latter possibility, hnRNPC and hnRNPA2B1 proteins that have been previously reported to function indirectly through an ‘m⁶A switch’ mechanism^40,41 were identified in mass spectrometry experiments as Xist RNA interactors⁸. Together with previous reports showing that m⁶A can promote nuclear RNA stability through YTHDC1 (refs. ^42,43), our findings underscore the complexity and context-dependent nature of m⁶A function in regulating nuclear RNA stability. Additional studies are required to fully elucidate the factors and pathways governing m⁶A-mediated nuclear RNA stability.

In conclusion, we find that the m⁶A pathway functions in conjunction with the NEXT complex to modulate Xist RNA turnover and thereby contributes to the feedback control mechanisms that determine Xist RNA levels during normal development.

Methods

Tissue culture

All mES cells were grown in feeder-dependent conditions on gelatinized plates at 37 °C in a 5% CO₂ incubator. Mitomycin C-inactivated mouse fibroblasts were used as feeders. mES cell medium consisted of DMEM (Thermo Fisher) supplemented with 10% fetal calf serum (Merck), 2 mM l-glutamine (Thermo Fisher), 1× nonessential amino acids (Thermo Fisher), 50 μM β-mercaptoethanol (Thermo Fisher), 50 g ml⁻¹ penicillin–streptomycin (Thermo Fisher) and 1 ml of medium conditioned with leukemia-inhibitory factor made in house. Xist expression was induced by the addition of 1 µg ml⁻¹ doxycycline (Dox) (Sigma-Aldrich, D9891) for 24 h. Protein of interest with FKBP12^F36V knock-in was trigged for degradation by the addition of dTAG-13 (100 nM) (gift from J. Bradner lab).

Molecular cloning and CRISPR–Cas9-mediated knock-in

We followed an established strategy for FKBP12^F36V knock-in²¹. Briefly, single guide RNA (sgRNA) targeting near the YTHDC1 or ZCCHC8 stop codon was designed by online tool CRISPOR⁴⁴ (http://crispor.tefor.net/); oligos were synthesized by Invitrogen and then cloned into pSpCas9(BB)-2A-Puro (PX459) V2.0 (Addgene, 62988) backbone following the instructions. A donor vector was built by Gibson assembly (New England Biolabs) of homology arms (~400 bp) PCR-amplified from genomic DNA and the FKBP12^F36V sequence amplified from plasmid pLEX_305-N-dTAG (Addgene, 91797)²⁰ or other coding sequences (for example, GFP–METTL3) described below. To achieve site-specific mutagenesis from the plasmid, we followed the protocol from the QuikChange Lightning site-directed mutagenesis kit (Agilent) or Gibson assembly. This strategy was used for generating the mES cell line with GFP–METTL3 or GFP–METTL3-D395A at the Rosa26 locus, as described below. The Cas9 sgRNA-containing plasmid and donor vector were cotransfected at a molar ratio of 1:6 into XX mES cells on a six-well plate using Lipofectamine 2000 according to the manufacturer’s protocol (Thermo Fisher). Transfected cells were passaged at different densities into three Petri dishes with feeders, 24 h after transfection. The next day, cells were subjected to puromycin selection (4.5 μg ml⁻¹) for 48 h and then grown in regular mES cell medium until mES cell colonies were ready to be picked and expanded. Western blot analysis was used to screen colonies for FKBP12^F36V knock-in as this results in slower mobility of the FKBP12^F36V-fused protein compared to the WT protein in an SDS–PAGE gel and disappearance of the WT band on western blot. Selected clones were further characterized by PCR of genomic DNA and Sanger sequencing to confirm correct knock-in and homozygosity. The karyotype status of the X chromosome was checked by PCR. The sensitivity of selected clones to dTAG-13 treatment was validated by western blot. A summary of clone names can be found in Supplementary Table 1. Primers used in this study are listed in Supplementary Table 2.

Complementation using METTL3 or catalytic mutant METTL3 transgenes in the Rosa26 locus

CRISPR–Cas9-mediated knock-in was used to integrate METTL3 or catalytic mutant METTL3^D395A (ref. ²⁴) transgenes into the Rosa26 locus. To distinguish transgene from endogenous METTL3 and FKBP12^F36V-tagged METTL3, we added a sequence encoding an in-frame N-terminal GFP tag. sgRNA (CGCCCATCTTCTAGAAAGAC) was used for targeted knock-in. METTL3-D395A was constructed by Gibson assembly. PCR and western blot were used for screening colonies. The expression and nuclear localization of the GFP–METTL3 fusion proteins were confirmed by fluorescence microscopy. Elimination of the X₁₂₉ chromosome occurred in several clones, as indicated in the figure legends. This did not preclude assaying relative silencing efficiency and Xist RNA levels in the presence and absence of Dox and dTAG-13.

Western blot

Total cell lysates or quantified cell fractionations were resolved on a polyacrylamide gel and transferred onto PVDF or nitrocellulose membrane by quick transfer. Membranes were blocked by incubating them for 1 h at room temperature in 10 ml of 5% w/v Marvell milk powder. Blots were incubated overnight at 4 °C with the primary antibody, washed four times for 10 min with PBST and incubated for 1 h with secondary antibody conjugated to horseradish peroxidase (HRP). After washing five times for 5 min with PBST, bands were visualized using enhanced chemiluminescence (GE Healthcare). TBP, SETDB1 and KAP1 served as loading controls. Antibodies used in this study were anti-METTL3 (Abcam, ab195352), anti-METTL14 (Sigma-Aldrich, HPA038002), anti-RBM15 (Proteintech, 10587-1-AP), anti-YTHDC1 (Sigma-Aldrich, HPA036462), anti-TBP (Abcam, ab51841), anti-WTAP (Proteintech, 10200-1-AP), anti-SETDB1 (Proteintech, 11231-1-AP), anti-ZCCHC8 (Proteintech, 23374-1-AP), anti-ZFC3H1 (Sigma-Aldrich, HPA007151) and anti-KAP1 (Abcam, ab10484), together with anti-rabbit IgG HRP donkey (Amersham, NA934V) and anti-mouse IgG HRP sheep (Amersham, NXA931V). Primary antibodies used for western blot were diluted at 1:1,000 whilst secondary antibodies were diluted at 1:2,000.

RNA-SPLIT

RNA-SPLIT was carried out as detailed previously²⁶. Briefly, mES cells were grown on gelatin-coated 18 × 18-mm no. 1.5H precision coverslips (±5 μm tol.; Marienfeld Superior) in a six-well plate on a layer of feeder cells. When the mES cells reached 60–70% confluency, Xist expression was induced for 1.5 or 24 h using 1 μg ml⁻¹ Dox. Cells were then incubated with 50 nM diAcFAM HaloTag ligand (488 nm, Promega) and 1 μg ml⁻¹ Dox for 45 min, before being washed with ES cell medium containing 1 μg ml⁻¹ Dox for 15 min. Next, different coverslips were incubated with 50 nM JF-585 HaloTag ligand (kindly provided by L. Lavis, Howard Hughes Medical Institute Janelia) and 1 μg ml⁻¹ Dox for different times to label newly synthesized Xist RNA molecules, (0, 60, 80, 100, 120, 140, 160, 180, 200 and 220 min to assess Xist turnover or 10, 20, 30, 40, 50 and 60 min to assess Xist RNA transcription dynamics) before being washed with PBS. Cells were fixed for 10 min at room temperature with 2% formaldehyde prepared fresh in PBS (pH 7) before a stepwise exchange to PBST (0.05% Tween-20) and permeabilization with 0.2% Triton X-100 for 10 min, followed by two washes with PBST. Subsequently, cells were incubated with 2 μg ml⁻¹ DAPI in PBST for 10 min, before being washed briefly with PBS followed by double-distilled H₂O. Cells were then mounted centrally on the unfrosted side of Superfrost Plus microscopy slides (VWR) using Vectashield soft mount medium, sealed with clear nail polish and imaged using the DeltaVision OMX V3 Blaze system (GE Healthcare). Images were analyzed as described previously²⁶, with all scripts and details of further script refinement to improve usability as detailed.

ChrRNA-seq

ChrRNA was extracted according to a previous study¹⁷. Briefly, control or treated mES cells from one confluent 15-cm dish were trypsinized and washed in PBS. Cells were lysed on cold ice in RLB buffer (10 mM Tris pH 7.5, 10 mM KCl, 1.5 mM MgCl₂ and 0.1% NP-40) and nuclei were purified by centrifugation through a sucrose cushion (24% sucrose in RLB). Pelleted nuclei were resuspended in NUN1 (20 mM Tris-HCl pH 7.5, 75 mM NaCl, 0.5 mM EDTA and 50% glycerol) and then lysed with NUN2 (20 mM HEPES pH 7.9, 300 mM, 7.5 mM MgCl₂, 0.2 mM EDTA and 1 M urea). Samples were incubated for 15 min on ice with occasional shaking and then centrifuged at 2,800g to isolate the insoluble chromatin fraction. The chromatin pellet was resuspended in TRIzol by passing through a 23G needle several times. Finally, ChrRNA was purified through standard TRIzol–chloroform extraction followed by isopropanol precipitation. Samples were treated with two rounds of Turbo DNaseI to remove the DNA contamination. The quality of the ChrRNAs were checked by RNA bioanalyzer. Approximately 250–750 ng of RNA was used for library preparation using the Illumina TruSeq stranded total RNA kit including the ribosomal RNA (rRNA) depletion step (RS-122-2301). Alternatively, Ribo-Magoff (Vazyme, N420) was used for rRNA removal. Libraries were quantified by qPCR with KAPA library quantification DNA standards (Kapa biosystems, KK4903). DNA and RNA concentrations were also determined by Qubit. The libraries were pooled and 2× 81-bp paired-end sequencing was performed using Illumina NextSeq 500 (FC-404-2002).

ChrRNA-seq data analysis

The ChrRNA-seq data mapping pipeline used in this study was similar to previous work¹⁷. Briefly, the raw FASTQ files of read pairs were first mapped to an rRNA build by bowtie2 (version 2.3.5 or 2.4.5)⁴⁵ and rRNA-mapped reads were discarded. The remaining unmapped reads were aligned to the ‘N-masked’ genome (mm10) with STAR (version 2.5.2b or 2.7.9a)⁴⁶ using parameters ‘--twopassMode Basic --outSAMstrandField intronMotif --outFilterMismatchNoverReadLmax 0.06 --outFilterMultimapNmax 1 --alignEndsType EndToEnd’ for all the sequencing libraries. Unique alignments were retained for further analysis. We made use of 23,005,850 SNPs between Cast and 129S genomes and used SNPsplit (version 0.4.0dev; Babraham Institute) to split the alignment into distinct alleles (Cast and 129S) using the parameter ‘--paired’. The (allelic) read numbers were counted by the program featureCounts (version 1.5.2) (‘-t transcript -g gene_id -s 2’)⁴⁷ and the alignments were sorted by SAMtools (version 1.16.1)⁴⁸. Files of bigWig were generated by BEDTools (version 2.27.1)⁴⁹ and visualized by Integrated Genomics Viewer (IGV; version 2.17.1)⁵⁰ or UCSC Genome Browser. The metagene profile and heat map were generated by deepTools (version 3.5.5)⁵¹ and custom Python scripts. For biallelic analysis, counts were normalized to 1 million mapped read pairs using the R package (version 4.1.0 or 4.2.1) edgeR. Genes with at least ten SNP-covering reads across all the samples were used to calculate the allelic ratio of Xi/(Xi + Xa). PCA was performed using the ‘prcomp’ function in R and plotted using the tidyverse (version 2.0.0) ggplot2 package. The allelic ratios of samples derived from SPEN knockout or deletion of Xist B/C-repeat were taken from the previous study¹⁷. Gene categories including initial X-linked gene expression level and promoter chromatin landscape were taken from previous studies^15,17 and gene silencing kinetics data were taken from another study²².

MeRIP-seq

MeRIP-seq was performed according to a previously described method⁵² with minor modifications. Briefly, total RNA was isolated from preplated mES cells according to the procedure above. RNA was fragmented by incubation for 6 min at 94 °C in thin-walled PCR tubes with fragmentation buffer (100 mM Tris-HCl and 100 mM ZnCl₂). Fragmentation was quenched using stop buffer (200 mM EDTA pH 8.0) and incubation on ice more than 1 min, before ensuring the correct size (~100 nt) using RNA Bioanalyzer. Approximately 300 μg of fragmented (~100 nt) RNA was incubated with 10 μg of anti-m⁶A antibody (Synaptic Systems, 202 003), RNasin (Promega), 2 mM VRC, 50 mM Tris, 750 mM NaCl and 5% IGEPAL CA-630 in DNA/RNA low-bind tubes for 2 h before m⁶A-containing RNA was isolated using 200 μl of protein A magnetic beads per immunoprecipitate (preblocked with BSA). After this 2-h incubation, extensive washing with 1× immunoprecipitation buffer (10 mM Tris-HCl pH 7.4, 150 mM NaCl and 0.1% NP-40), 2× low-salt buffer (50 mM Tris-HCl pH 7.4, 50 mM NaCl, 1 mM EDTA, 1% NP-40 and 0.1% SDS), 2× high-salt buffer (50 mM Tris-HCl pH 7.4, 1 M NaCl, 1 mM EDTA, 1% NP-40 and 0.1% SDS and 1× immunoprecipitation buffer was performed to remove the unspecific binding. Next, 6.7 mM m⁶A (Sigma-Aldrich) was used to elute RNA from the beads. Input and eluate samples were coprecipitated with ethanol and Glycoblue, quantified and pooled as libraries generated using TruSeq Stranded total RNA LT sample prep according to the manufacturer’s instructions but skipping the fragmentation step. Finally, 75-bp single-end reads were obtained using Illumina NextSeq 500.

MeRIP-seq data analysis

MeRIP-seq data analysis procedure was similar to ChrRNA-seq regarding the raw FASTQ read mapping. After mapping, sequencing reads were split into positive and negative strands using SAMtools (version 1.16.1)⁴⁸ and bigWig files were generated accordingly. A total of 10 million mapped reads per library were used to perform normalization. The previously defined m⁶A peak regions²¹ including those on Xist RNA were taken for m⁶A intensity analysis, which is calculated as log₂(immunoprecipitate/input) with peak intensity close to 0 or less than 0 indicating no m⁶A enrichment. The selected peaks are visualized by IGV (version 2.17.1)⁵⁰.

Total RNA-seq

METTL3 FKBP12^F36V-tagged cells (C3 and H5) were either treated with dTAG-13 for 26 h or not. Cells were washed with PBS twice and directly lysed with TRIzol, followed by total RNA isolation as described for ChrRNA-seq. DNA contamination was removed by Turbo DNase I treatment. The quality of the RNAs was checked by RNA bioanalyzer. Approximately 500 ng of total RNA was used for library preparation using the Illumina TruSeq stranded total RNA kit including the rRNA depletion step (RS-122-2301). The libraries were pooled and 2× 81-bp paired-end sequencing was performed using Illumina NextSeq 500 (FC-404-2002).

Total RNA-seq data analysis

The total RNA-seq data analysis procedure was similar to that for ChrRNA-seq regarding the raw FASTQ reads mapping. PCR duplicates were removed using the Picard (version 2.25.0) command MarkDuplicates. Differentially expressed genes and transposable elements were called by TEtranscripts (version 2.2.1)⁵³ with default parameters. Upregulated and downregulated genes called were further cross-compared with m⁶A annotations from previous studies^21,54.

SLAM-seq

SLAM-seq was performed using the SLAM-seq kinetics kit catabolic kinetics module (Lexogen, 062.24) as previously described²⁶ and shown in Extended Data Fig. 6a. Specifically, cells were grown in gelatin-coated six-well plates after preplating to discard feeder cells. When reaching 60–70% confluency, cells were either untreated or treated with dTAG-13 for 2 h, followed by additional 1 μg ml⁻¹ Dox induction for 20 h. Transcribed RNA was then labeled with 4sU by incubation with medium containing 500 μM 4sU (Lexogen) and 1 μg ml⁻¹ Dox for another 4 h. The 4sU was withdrawn for all samples by medium washout. Different samples were washed with medium containing 1 μg ml⁻¹ Dox and 50 mM uridine (in excess, Lexogen) for 1.5 and 3 h. Cells were washed with PBS once and immediately lysed with TRIzol–chloroform for total RNA isolation. Equal amounts of RNA (5 μg) were treated with iodoacetamide to modify the 4-thiol group of S4U-containing nucleotides through the addition of a carboxyamidomethyl group by the SLAM-seq Kinetics Kit (Lexogen). The RNA was recovered using RNAClean XP beads (Beckman Coulter), followed by resuspension in nuclease-free water. Approximately 500 ng of RNA from each sample was taken forward for library preparation using the Illumina TruSeq stranded total RNA kit (RS-122-2301). Quantification of the libraries was conducted by qPCR using KAPA library quantification DNA standards (Kapa Biosystems, KK4903). Finally, the libraries were pooled and 2× 81-bp paired-end sequencing was performed using Illumina NextSeq500 (FC-404-2002).

SLAM-seq data analysis

Estimation of RNA half-life was performed using GRAND-SLAM⁵⁵. Briefly, the paired-end sequencing reads were first aligned to rRNA and then the unmapped reads were mapped to mouse genome mm10 by STAR (version 2.5.2b)⁴⁶ with the key parameters ‘--twopassMode Basic --outSAMstrandField intronMotif --outSAMattributes All --outFilterMultimapNmax 1 --outFilterMismatchNoverReadLmax 0.06 --alignEndsType EndToEnd’. Given that T-to-C conversion is the signature of SLAM-seq, the T-to-C conversion rate was calculated as 4sU incorporation and the average of all remaining conversions was calculated as background because of errors from sequencing or library preparation. The T-to-C conversion rate and background rate were calculated accordingly for each sample. The RNA decay was assumed to follow an exponential model; thus, the corresponding background corrected T-to-C conversion rates were fitted to the exponential model to estimate Xist RNA half-life.

Reporting summary

Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.

Data availability

High-throughput raw sequencing data and key processed data, including ChrRNA-seq, SLAM-seq, MeRIP-seq and total RNA-seq, were deposited to the National Center for Biotechnology Information’s Gene Expression Omnibus (GEO) under accession number GSE279269. The mouse genome (mm10) sequence and gene annotation were downloaded from UCSC genome browser (https://hgdownload.soe.ucsc.edu/downloads.html). The whole-genome collections of SNPs and short indel variants for mouse strains 129S1 and Cast/EiJ (mpg.v5) were downloaded from the mouse genome project (https://www.sanger.ac.uk/data/mouse-genomes-project/). Gene categories including initial X-linked gene expression level were taken from the GEO under accession number GSE119602. Gene silencing kinetics data were taken from the GEO under accession number GSE185843. The promoter chromatin landscape of mm10 genome was retrieved from GitHub (https://github.com/guifengwei/ChromHMM_mESC_mm10). Source data are provided with this paper.

Code availability

Key parameters used for sequencing data analysis are detailed in the Methods. The RNA-SPLIT analysis code was deposited to GitHub (https://github.com/HollyRoach/Automated_RNA-SPLIT).

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Acknowledgements

We are grateful to F. Constantinescu for assistance with mES cell tissue culture during pandemic, to J. Bowness for helping with the initial RNA-seq library preparation, to A. Cawte for helping with construct design for knock-in at the Rosa26 locus, to Y. Zhang for quantifying site-specific m⁶A changes on Xist and to all the N.B. lab members for fruitful discussions. Imaging was carried out at the Micron Oxford Advanced Bioimaging Unit, Department of Biochemistry, University of Oxford. We thank Oxford Biochemistry IT support for computing server maintenance. We thank B. Moindrot for critical reading of the manuscript. This work is supported by Wellcome Trust (215513/Z/19/Z to N.B.) and UKRI (EP/Y029062/1 to N.B.). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

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Holly L. Roach
Present address: Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK

Authors and Affiliations

Developmental Epigenetics, Department of Biochemistry, University of Oxford, Oxford, UK
Guifeng Wei, Heather Coker, Lisa Rodermund, Mafalda Almeida, Holly L. Roach, Tatyana B. Nesterova & Neil Brockdorff

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Guifeng Wei
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Heather Coker
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Lisa Rodermund
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Mafalda Almeida
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Holly L. Roach
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Tatyana B. Nesterova
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Neil Brockdorff
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Contributions

G.W. and N.B. conceptualized the study. G.W., with assistance from M.A., L.R. and T.B.N., generated the dTAG degron cell lines. G.W. conducted the ChrRNA-seq, SLAM-seq, total RNA-seq and MeRIP-seq and performed all sequencing data analyses. L.R., under the supervision of H.C. and N.B., developed RNA-SPLIT and applied it to Xist in this study. H.C., H.L.R. and L.R. analyzed the RNA-SPLIT data and produced the plots. N.B. and G.W. drafted the manuscript with contributions from coauthors. All authors read and approved the manuscript. N.B. supervised the entire project.

Corresponding authors

Correspondence to Guifeng Wei or Neil Brockdorff.

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The authors declare no competing interests.

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Supplementary Data 1

Statistical source data for Supplementary Fig. 1.

Supplementary Data 2

Statistical source data for Supplementary Fig. 2.

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Wei, G., Coker, H., Rodermund, L. et al. m⁶A and the NEXT complex direct Xist RNA turnover and X-inactivation dynamics. Nat Struct Mol Biol (2025). https://doi.org/10.1038/s41594-025-01663-w

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Received: 21 October 2024
Accepted: 04 August 2025
Published: 09 September 2025
DOI: https://doi.org/10.1038/s41594-025-01663-w