GABPA Recruits the Integrator Endonuclease Complex to Promote Transcription Elongation

GABPA Recruits the Integrator Endonuclease Complex to Promote Transcription Elongation | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article GABPA Recruits the Integrator Endonuclease Complex to Promote Transcription Elongation Chunxia Zhang, Hang Yang, Jinjing Geng, Wusa Baqie This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7297262/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted You are reading this latest preprint version Abstract Transcription factors (TFs) coordinate gene regulatory programs essential for cell identity and fate, yet the mechanisms by which individual TFs modulate distinct stages of transcription remain incompletely understood. GABPA, an ETS family transcription factor, was recently identified as a critical regulator of naïve pluripotency in mouse embryonic stem cells (mESCs), but its molecular functions have remained elusive. Here, we employ an acute protein degradation system to dissect GABPA activity with high temporal resolution, enabling the identification of immediate transcriptional targets and mechanisms while avoiding secondary effects associated with conventional gene knockouts. We find that GABPA is essential for mESC viability through a previously unrecognized mechanism that is independent of its canonical heterotetrameric partner, GABPB. Mechanistically, GABPA physically engages the INTS4/9/11 endonuclease module of the Integrator complex to facilitate RNA polymerase II (Pol II) pause-release at ribosome biogenesis genes, promoting productive transcription elongation. Acute GABPA depletion leads to a marked reduction of gene body-associated Ser2-phosphorylated Pol II, indicative of defective elongation. In contrast, prolonged GABPA loss results in diminished chromatin accessibility and enhancer activity at pluripotency-associated loci. Together, these findings reveal dual temporally distinct roles for GABPA, an immediate function in transcriptional elongation and a later function in chromatin regulation. Our study redefines GABPA as a multifaceted transcriptional regulator acting independently of GABPB, and provides a framework for temporally resolved dissection of TF function in stem cell biology. Biological sciences/Genetics/Gene regulation Biological sciences/Developmental biology/Stem cells/Embryonic stem cells GABPA INTAC transcription elongation Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction Transcriptional regulation is a fundamental process that governs cell identity and function, enabling dynamic control of gene expression programs throughout development, homeostasis, and disease. This multilayered process involves the coordinated recruitment and activity of transcriptional machinery at gene promoters and enhancers, and spans distinct stages including transcription initiation, promoter-proximal pausing, productive elongation, and termination. Transcription factors (TFs) play central roles in orchestrating this process by reading genomic regulatory sequences and translating them into context-specific transcriptional outputs(Stadhouders et al., 2019 ; Takahashi et al., 2007 ). Most TFs are modular in structure, comprising a sequence-specific DNA-binding domain (DBD) and an effector domain (ED) responsible for modulating transcriptional activity(Lambert et al., 2018 ; Soto et al., 2022 ). Effector domains are commonly classified into activator domains (ADs), repressor domains (RDs), or bifunctional modules that mediate both functions. Through these domains, TFs engage cofactors, chromatin remodelers, histone-modifying enzymes, and the general transcription machinery to control RNA polymerase II (Pol II) recruitment, chromatin accessibility, and transcriptional output(Isbel et al., 2022 ; Spitz and Furlong, 2012 ). GABPA (GA-binding protein alpha), a member of the ETS transcription factor family, binds to DNA via a conserved ETS domain and is broadly expressed across mammalian cell types(Sharrocks, 2001 ). Canonically, GABPA forms a heterotetramer with one of two transcriptionally active β-subunits, GABPB1 or GABPB2, which harbor transcriptional activation domains (TADs) that mediate cofactor interactions and gene activation(Thompson et al., 1991 ). In addition to its canonical partners, GABPA has been shown to cooperate with various cofactors in a context-dependent manner. For example, in myeloid cells, GABPA recruits the retinoic acid receptor to target promoters via p300-dependent enhanceosome assembly(Resendes and Rosmarin, 2006 ). while in the brain, the methyltransferase METTL23 interacts with GABPA to regulate cognition-related gene expression(Reiff et al., 2014 ). Moreover, in vitro studies have demonstrated that GABPA physically bound to the DNA binding domain of ATF1, forming a ternary complex composed of ATF1, GABPA and GABPB(Sawada et al., 1999 ). Despite these diverse interaction profiles, the molecular mechanism by which GABPA regulates transcription has remained poorly understood. Our recent work identified GABPA as a key regulator of naïve pluripotency establishment in mouse embryonic stem cells (mESCs)(Zhou et al., 2025 ), raising new questions about its mechanism of action in this context. However, conventional genetic approaches such as gene deletion or RNA interference have limited temporal resolution, often confounding direct TF targets with secondary transcriptional and epigenetic responses that emerge over time. Acute protein degradation technologies, including the auxin-inducible degron (AID) system(Nishimura et al., 2009 ) and the degradation tag (dTAG) system (Abuhashem et al., 2022 ; Nabet et al., 2018 ), provide a powerful alternative by enabling rapid and selective depletion of proteins, thereby allowing interrogation of immediate and primary regulatory events. In this study, we applied the dTAG system to acutely degrade GABPA in mESCs and performed time-resolved transcriptomic and chromatin profiling to define its direct transcriptional roles. Strikingly, we uncovered a non-canonical function of GABPA in promoting transcriptional elongation independent of GABPB1/B2. Mechanistically, we show that GABPA physically associates with the Integrator complex, specifically its catalytic endonuclease module (INTS4/9/11), and facilitates its recruitment to promoter-proximal regions of GABPA target genes. Acute GABPA depletion led to a rapid and selective loss of Pol II Ser2 phosphorylation within gene bodies, consistent with defective pause-release and elongation. These findings position GABPA as an essential scaffold linking sequence-specific transcriptional targeting to the elongation machinery, thereby extending the functional repertoire of ETS family TFs. More broadly, this study illustrates how TFs can regulate gene expression through elongation-phase mechanisms that are independent of chromatin accessibility or initiation control, offering new insight into the principles of transcriptional regulation in mammalian stem cells. Results GABPA regulates mESC survival in a GABPB1/B2-independent way Our previous work identified GABPA as a key regulator in the establishment of naïve pluripotency. However, the mechanisms by which GABPA governs gene expression remain poorly understood. To define its direct function, we generated GABPA-dTAG mESCs(Zhou et al., 2025 ). Consistent with phenotypes reported in Gabpa conditional knockout mice(Ueda et al., 2017 ), GABPA depletion led to rapid cell death, with cells failing to survive beyond 24 hours (Fig. 1 , A and B, fig. S1 A). Notably, time-course analysis revealed that hallmarks of apoptosis and cell cycle dysregulation emerged as early as 9 hours post-GABPA depletion (fig. S1 , B and C), preceding overt cell death. Taken together, these findings establish GABPA as a core survival factor in mESCs and highlight the utility of acute depletion strategies in dissecting its immediate regulatory functions, bypassing the confounding secondary effects associated with chronic loss-of-function models. GABPA is canonically known to function as a DNA-binding subunit that forms a heterotetrameric complex with GABPB1 or GABPB2, both of which have the trans-activator domain. During mouse early embryonic development, the expression of Gabpa and Gabpb1 reach to peak from late 2 cell stage, whereas Gabpb2 remains expressed at consistently low levels throughout this window (fig. S1 D), suggesting that GABPB1 is the predominant cofactor for GABPA in early embryos and potentially in mESCs. To directly test whether GABPA requires GABPB1 to maintain mESC viability, we generated a GABPB1-dTAG mESC line enabling acute degradation of GABPB1 protein (fig. S1 E). Surprisingly, GABPB1 depletion had minimal impact on mESC survival and proliferation, as cells remained viable and morphologically indistinguishable from controls over extended culture (Fig. 1 , A and B). This unexpected observation prompted us to examine potential compensation by GABPB2. Although Gabpb2 expression is low, we simultaneously targeted both GABPB1 and GABPB2 using the dTAG system (fig. S1 F). Dual depletion impaired cell proliferation, but the phenotype was substantially milder and occurred later than that observed following GABPA loss (Fig. 1 , A and B). These findings suggest that while GABPB1 and GABPB2 may contribute partially to GABPA function, GABPA may possess GABPB-independent functions critical for mESC viability. Furthermore, transcriptome analysis after 12 hours of protein degradation (fig. S1 G, table S1 ) revealed that GABPA depletion resulted in widespread transcriptional dysregulation, with approximately 1,500 differentially expressed genes (DEGs), including both up- and downregulated genes (Fig. 1 C), GABPB1 depletion alone had a negligible effect on gene expression, resulting in only 57 DEGs (Fig. 1 D). Combined depletion of GABPB1 and GABPB2 increased the number of DEGs to 246, yet the overall transcriptional impact remained modest compared to the extensive changes triggered by GABPA loss (Fig. 1 E). Moreover, a substantial proportion of genes downregulated upon GABPB1 or GABPB1/B2 depletion were also downregulated following GABPA loss (Fig. 1 F, fig. S1 H), suggesting that the transcriptional activity of GABPB1/B2 depends on the presence of GABPA. However, the vast majority of GABPA-regulated genes were unaffected by the loss of either or both cofactors, indicating that GABPA controls a large gene regulatory network independently of its conventional heterotetrameric partners during this time window. Collectively, these findings demonstrate that GABPA is the primary driver of the transcriptional program required for mESC survival in an unanticipated, GABPB1/B2-independent mode of action. GABPA interacts with core transcriptional machinery in mESCs To uncover potential cofactors that collaborate with GABPA to support mESC survival, we performed immunoprecipitation followed by mass spectrometry (IP-MS) in GABPA-dTAG mESCs using an HA antibody to selectively enrich endogenous GABPA complexes (fig. S2 , A and B). Comparison between the DMSO-treated control and the dTAG-induced GABPA-depleted group revealed 175 proteins significantly enriched in the presence of GABPA (Fig. 2 A, table S2 ), representing candidate GABPA interactors. As expected, the most highly enriched proteins were GABPB1 and GABPB2, in line with the canonical model in which GABPA forms a DNA-binding heterotetramer with GABPB subunits to drive transcription (Fig. 2 A). Interestingly, several previously reported GABPA interactors, such as Sp1 and CBP/P300 in myeloid cells(Bush et al., 2003 ), and Mettl23 in neuroblasts(Reiff et al., 2014 ), were not detected in the mESC GABPA interactome, suggesting that GABPA engages in highly cell type-specific protein-protein interactions. Functional annotation of the 175 enriched proteins revealed that GABPA predominantly associates with factors involved in transcription regulation, chromatin organization, and RNA processing (Fig. 2 , A and B). Notably, components of the transcription elongation and pause-release machinery were among the top interactors, including INTS4, SPT5, and LARP7 (Fig. 2 B). INTS4 serves as the scaffold subunit of the catalytically active endonuclease module of the Integrator complex (containing INTS4/9/11)(Elrod et al., 2019 ; Zheng et al., 2020 ). SPT5 is a multifunctional regulator and its rapid depletion caused a reduction of paused Pol II at promoter-proximal region (Aoi et al., 2021 ; Hu et al., 2021 ). LARP7 is a 3’RNA stability protein and it stably associated with the 7SK snRNP to regulate P-TEFb activity(Krueger et al., 2008 ). Of particular interest, INTS4/9/11 complex were recently shown to be essential for mESC survival(Hu et al., 2023 ), mirroring the phenotype observed upon GABPA loss. To validate these interactions, we performed endogenous co-immunoprecipitation (Co-IP) using HA antibodies in GABPA-dTAG mESCs. Consistent with the mass spectrometry results, HA-tagged GABPA robustly co-immunoprecipitated with INTS4, as well as INTS11, the catalytic subunit of the Integrator endonuclease module (Fig. 2 , C and D). In addition, GABPA also interacted with RNA polymerase II (Fig. 2 C), suggesting a potential role in transcriptional regulation through recruitment or modulation of the transcriptional machinery. Several additional interactors involved in RNA metabolism and chromatin regulation, including ANLN, DDX21, NPM1, and SPT5, were also validated via Co-IP (fig. S2 C), corroborating the specificity of the GABPA interactome. To investigate whether these physical interactions are functionally relevant, we examined the chromatin occupancy of GABPA and its interactors. Chromatin profiling revealed that a large proportion (56%) of GABPA-bound genomic loci were co-occupied by INTS11, particularly at promoter-proximal region (Fig. 2 E). Motif enrichment analysis of INTS11 peaks further revealed a strong overrepresentation of ETS motifs (Fig. 2 F), suggesting that GABPA may serve as a DNA-targeting factor for the Integrator complex. Together, these findings identify the INTS4/9/11 module as a previously unrecognized effector of GABPA function in mESCs and uncover a potential mechanistic link between TF-mediated chromatin binding and Integrator-driven transcriptional control. GABPA recruits INTS4/9/11 complex to regulate the expression of ribosome biogenesis related genes Although the Integrator complex plays key roles in transcriptional regulation, its recruitment mechanisms remain unclear due to the absence of intrinsic DNA-binding domains. Recent structural evidence indicates that TFs can serve as chromatin-recruiting platforms for Integrator via direct protein-protein interactions(Razew et al., 2024 ). Given the physical interaction between GABPA and the INTS4/9/11 endonuclease module, we hypothesized that GABPA may function as a DNA-anchored recruiter of Integrator to support gene expression programs essential for mESC viability. To further investigate how GABPA cooperates with the INTS4/9/11 module to regulate gene expression, we performed SLAM-seq to monitor global nascent transcription following GABPA depletion (fig. S3 A). Cells were treated with dTAG for 12 hours, a time point chosen to capture early transcriptional changes prior to widespread cell death. This analysis identified 2,820 differentially expressed genes (DEGs), of which a striking 94.5% were downregulated (Fig. 3 A). Among these downregulated genes, approximately 18% belonged to the early post-implantation (EPI) gene set (fig. S3 B), consistent with our previous findings implicating GABPA function in the establishment of naïve pluripotency(Zhou et al., 2025 ). Gene ontology (GO) enrichment analysis revealed that GABPA-activated genes are significantly associated with biological processes involved in ribonucleoprotein complex biogenesis and RNA processing (Fig. 3 B), suggesting a role for GABPA in coordinating biosynthetic and growth-related pathways critical for mESC viability. To determine whether these effects were mediated by direct GABPA binding, we integrated SLAM-seq data with GABPA CUT&RUN profiles. Remarkably, 47% of the GABPA-responsive DEGs were directly bound by GABPA (Fig. 3 , C and D). There was a strong positive correlation between the extent of nascent RNA downregulation and the number of canonical GABPA binding motifs within promoter regions (Fig. 3 E, fig. S3 C), supporting a model of direct transcriptional regulation. To further elucidate the mechanistic link between GABPA and the Integrator complex, we compared the transcriptional profiles of mESCs following acute depletion of GABPA (this study) and INTS11(Wang et al., 2023 ). Although only around 25% of DEGs overlapped in these two groups (Fig. 3 F), GO analysis of the overlapping DEGs revealed a pronounced enrichment for genes involved in ribonucleoprotein complex biogenesis (Fig. 3 G), consistent with the notion that GABPA may recruit the Integrator complex to control this essential biosynthetic program. To directly test whether GABPA facilitates the chromatin recruitment of the INTS4/9/11 complex, we performed CUT&Tag profiling of INTS11 in control and GABPA-depleted mESCs. Strikingly, GABPA depletion led to a marked global reduction of INTS11 occupancy at shared target genes (fig. S3 A, Fig. 3 , H and I), indicating that GABPA is required for stable association of the INTS4/9/11 complex with chromatin. Taken together, these data support a model in which GABPA functions as a chromatin-anchored recruiter of the INTS4/9/11 module to activate transcription of genes essential for RNA processing and ribonucleoprotein complex assembly. Acute depletion of GABPA leads to blockage of RNA Pol II elongation Given that GABPA protein is efficiently depleted within 1 hour of dTAG treatment (fig. S1 A), we next sought to distinguish primary transcriptional responses from secondary downstream effects. To this end, we conducted time-resolved SLAM-seq at 1, 2, and 4 hours post-GABPA depletion to monitor nascent RNA dynamics and identify genes directly responsive to acute GABPA loss (fig. S4 A, table S3 ). Strikingly, as early as 1 hour post-depletion, we detected significant downregulation of 100 genes (Fig. 4 A), indicating that GABPA controls a set of genes with rapid and direct transcriptional sensitivity to its absence. The number of downregulated genes increased in a time-dependent manner, with 281 and 498 genes significantly downregulated at 2 and 4 hours, respectively (Fig. 4 , B to E, fig. S4 B), consistent with an expanding transcriptional cascade triggered by GABPA loss. Notably, GO analysis revealed a consistent and strong enrichment for genes involved in ribonucleoprotein complex biogenesis across all early time points (Fig. 4 F, fig. S4 , C and D). And the GABPA CUT&RUN signals are enriched around the TSS of significantly down-regulated genes at 1, 2, and 4 hours (fig. S4 E). These findings closely mirror the transcriptional landscape observed at the 12-hour time point (Fig. 3 C), suggesting that GABPA rapidly activates a core transcriptional program critical for RNA processing, ribosome assembly, and cellular fitness in mESCs. To determine whether these early transcriptional effects were accompanied by changes in chromatin state, we assessed chromatin accessibility and active histone modifications after acute GABPA depletion. ATAC-seq and CUT&Tag profiling of H3K27ac and H3K4me3 were performed at 1 hour post-treatment (fig. S5A). In contrast to the transcriptional repression observed, no significant changes were observed in global chromatin accessibility or histone modification levels at this early time point (fig. S5, B to D). These results suggest that GABPA does not regulate gene expression by remodeling chromatin structure or enhancer/promoter activation during the immediate early response. Given the physical and functional interaction between GABPA and the INTS4/9/11 complex, we next asked whether GABPA acute depletion affect the Integrator endonuclease module recruitment to promoter-proximal region. To address this, we profiled INTS11 occupancy at 1 hour post-GABPA depletion using CUT&Tag. Notably, INTS11 binding at promoter-proximal regions of the 100 rapidly downregulated genes was significantly reduced following GABPA acute depletion (Fig. 5 , A to D). Given that Integrator endonuclease module has been previously implicated in facilitating transcriptional elongation(Hu et al., 2023 ), we then hypothesized that GABPA may regulate gene expression in mESCs by promoting transcription elongation. To test this, we examined the distribution of RNA polymerase II (Pol II) phosphorylation marks using CUT&Tag, focusing on Serine 5-phosphorylated (pSer5) and Serine 2-phosphorylated (pSer2) forms, which are enriched at transcription start sites (TSSs) and gene bodies, respectively, and serve as proxies for initiation and elongation states. Upon acute GABPA depletion, we observed no substantial change in either pSer5 or pSer2 occupancy at promoter regions of GABPA target genes (Fig. 5 , E to G), suggesting that Pol II recruitment and initiation remain largely intact. In contrast, pSer2 signal within gene bodies was markedly reduced (Fig. 5 , E to G), indicating a defect in productive transcriptional elongation. This selective loss of gene body associated Pol II pSer2 signal, in the absence of chromatin accessibility or histone mark alterations, suggests that GABPA cooperates with INTS4/9/11 complex to regulate transcription through a mechanism that facilitates Pol II elongation. Prolonged GABPA depletion impairs chromatin accessibility and general transcription machinery While acute GABPA loss primarily disrupts transcription elongation without affecting chromatin accessibility, we next asked whether prolonged depletion impacts chromatin state. To address this, we performed ATAC-seq and CUT&Tag for H3K27ac and H3K4me3 following 12 hours of GABPA depletion (fig. S6, A to C). Cells were harvested 12 hours after dTAG treatment to capture early chromatin changes prior to extensive cell death. Genome-wide ATAC-seq analysis revealed a modest yet significant reduction in chromatin accessibility at promoter region of GABPA-affected genes (Fig. 6 , A to C), indicating that GABPA contributes to the maintenance of an open chromatin state. CUT&Tag profiling further demonstrated concordant decreases in both H3K27ac and H3K4me3 signal intensities at these loci (Fig. 6 , A to C), hallmark modifications of transcriptionally active chromatin. These data suggest that GABPA may facilitate the epigenetic landscape conducive to gene expression. To determine whether GABPA affects core components of the transcriptional machinery, we examined RNA Pol II phosphorylation status. Western blot analysis revealed a pronounced reduction in both Ser5 and Ser2 phosphorylation after GABPA depletion for 12 hours (Fig. 6 D), indicative of impaired transcriptional initiation and elongation, respectively. Consistently, the protein levels of CDK7 and CDK9, cyclin-dependent kinases essential for Pol II CTD phosphorylation during promoter clearance and productive elongation, were also markedly decreased (Fig. 6 D). Consistently, CUT&Tag for pSer5 and pSer2 also showed significant decrease of pSer5 and pSer2 signal intensities at promoter and gene body, respectively (Fig. 6 B). These observations raise the possibility that GABPA may interface with broader regulatory networks beyond Integrator. Indeed, our IP-MS analysis identified multiple putative GABPA interactors involved in transcriptional regulation and epigenetic modification (Fig. 2 B), suggesting that its role in sustaining the transcriptional machinery may extend beyond its immediate impact on pause release. Collectively, these results demonstrate that GABPA maintains mESC transcription through temporally distinct mechanisms: an immediate role in promoting Pol II pause-release and transcription elongation via Integrator complex recruitment, followed by a later role in sustaining chromatin accessibility, active histone modifications, and the phosphorylation state of Pol II and its associated kinases. Together, these functions establish GABPA as a central regulator of transcriptional competence in mESCs. Discussion The dynamic regulation of gene expression by TFs is central to cellular identity and function. Yet, defining the immediate molecular consequences of TF loss has remained challenging due to compensatory adaptations that arise with conventional gene deletion or knockdown strategies. These long-term perturbations often blur the distinction between direct and indirect effects by allowing time for secondary transcriptional and epigenetic remodeling. In this study, we leveraged an acute degradation system to dissect the primary transcriptional roles of the ETS family transcription factor GABPA in mESCs, revealing an unanticipated function in the regulation of transcriptional elongation through interaction with the Integrator complex. By degrading GABPA within 1 hour, we captured early and direct transcriptional responses to its loss while minimizing secondary adaptations. Time-resolved SLAM-seq analysis revealed that GABPA is required for the rapid transcriptional activation of a core gene module, predominantly composed of ribonucleoprotein biogenesis and RNA processing genes. These transcriptional effects preceded any detectable changes in chromatin accessibility or active histone modifications, arguing strongly against GABPA acting through canonical chromatin remodeling or enhancer priming mechanisms during this early response phase. Instead, our data point to a distinct mechanism by which GABPA modulates transcriptional output. We identified a physical and functional interaction between GABPA and the INTS4/9/11 endonuclease module of the Integrator complex, a multifunctional regulator known to promote Pol II elongation. Consistently, acute GABPA depletion led to a global reduction in INTS11 occupancy at shared target genes, implicating GABPA as a key recruiter of the Integrator endonuclease complex to chromatin. Functionally, this recruitment appears to be critical for proper transcriptional elongation. Our integrative analysis revealed that acute GABPA depletion selectively impaired RNA Pol II elongation dynamics. While Pol II initiation remained largely unaffected, gene body-associated pSer2 levels were markedly reduced at GABPA target genes. This supports a model in which GABPA recruits Integrator to facilitate the transition from paused to elongating Pol II, thereby ensuring productive transcription of genes critical for mESC viability (Fig. 7 ). Notably, this elongation-centered role of GABPA diverges from classical paradigms in which TFs primarily modulate chromatin accessibility or initiation complex assembly. Our findings thus expand the conceptual framework for transcriptional regulation by TFs, illustrating how a sequence-specific DNA-binding factor can exert gene-selective effects through elongation-phase control. In this context, the rapid downregulation of ribosome biogenesis genes following GABPA depletion suggests that these loci are particularly reliant on uninterrupted elongation, positioning them as early sensors of transcriptional stress in stem cells. Beyond this primary mechanism, our GABPA interactome analysis revealed additional cofactor, including SPT5, LARP7, NPM1, ANLN, and DDX21, that may contribute to broader transcriptional and RNA processing networks. Intriguingly, prolonged depletion of GABPA resulted in widespread transcriptional dysregulation, potentially mediated by these alternative interactors, raising the possibility that GABPA serves as a multifaceted scaffold coordinating multiple layers of gene expression control. This is further supported by the phenotypic disparity observed between GABPA and GABPB1/B2 depleted mESCs. While GABPA is canonically known to function as a heterotetramer with GABPB1 or GABPB2, our data and prior studies suggest that GABPA harbors additional functions independent of its known partners, possibly via interaction with other chromatin associated proteins. In summary, our findings identify GABPA as a critical regulator of transcriptional elongation in mESCs and establish a direct mechanistic link between DNA-bound transcription factors and the elongation machinery. This work not only redefines the functional repertoire of GABPA but also highlights the power of acute perturbation strategies in resolving primary transcriptional regulatory mechanisms. More broadly, our work suggests that TF-driven modulation of Pol II elongation dynamics represents an underappreciated axis of gene regulation, particularly relevant for sustaining the biosynthetic demands of rapidly proliferating cells such as pluripotent stem cells. Methods Cell culture The ES-B6 cells (from National Stem Cell Resource Center) were cultured on 0.1% gelatin-coated plates with 2i/LIF (MEKi/GSK3i/leukemia inhibitory factor) condition. Cells were grown in DMEM-high glucose (Gibco 11960044), supplemented with 15% fetal bovine serum (FBS)(Gibco 10099141, VISTECH SE200-ES), 100 U/mL penicillin–streptomycin (Gibco, 15140122), 2 mM L-Glutamine (Life technologies A2916801), 1 mM sodium pyruvate (MP Biomedicals, 219965480), 0.084 mM 2-mercaptoethanol (Gibco, 21985023), 1× MEM NEAA (Life technologies, 11140050), 1,000 IU/mL LIF (Sigma-Aldrich, ESG1107), 0.5 µM PD0325901 (Millipore, 444966-5mg), and 3 µM CHIR99021 (Selleck, S1263). Genome editing for dTAG endogenous knock-in To establish Gabpa dTAG/dTAG and Gabpb1 dTAG/dTAG cells by the endogenous knock-in, Gabpa- HAL-FKBP F36V -2xHA-HAR, Gabpb1- HAL-FKBP F36V -2xHA-HAR and px330 plasmids were transfected into mESCs with Lipofectamine™ 2000 (Invitrogen, 11668030). Primers for plasmid construction are listed in table S4 . 24 hours after transfection, cells were selected with 1 µg/mL puromycin (Invitrogen, A1113803) for another 48 hours. Then cells were cultured in puromycin-free medium for one week. Single-clone colonies were picked, expanded, and genotyped by genomic DNA PCR targeting the integration site. For homogeneous knock-in clones, protein degradation efficiency was verified by 500nM dTAG-13 treatment for 1 hour followed by Western Blotting. Gabpb1 dTAG/dTAG cells were used as the parental line to generate Gabpb1/b2 dTAG/dTAG cells following the similar process described above. Western blot A total of 1× 10 6 cells were lysed in 100 µL RIPA lysis buffer and incubated on ice for 30 mins. The lysate was centrifuged at 120,00 rpm for 30 mins at 4°C and the supernatant was collected. Protein extracts were quantified by BCA protein assay kit (Thermo Scientific, 23227), following manufacturer’s instructions. 90 µL of supernatant was mixed with 12.5 µL 5× loading buffer, and heated at 98°C for 15 mins. Samples were run on Precast Protein Plus Gel, 4–12%, Bis-Tris (Yeasen, 36269ES10) and transferred onto polyvinylidene fluoride transfer (PVDF) membrane. Primary antibodies used included anti-GABPA (1:4,000, Proteintech, 21542-1-AP), anti-HA (1:1,000, Cell Signaling Technology, 3724S and 2367S), anti-Flag (1:1,000, Proteintech, 66008-4-Ig), anti-GAPDH (1:5,000, Abmart, M20006M), anti-β-actin (1:5,000, Cell Signaling Technology, 4967S), Pol II (1:1000, Cell Signaling Technology, 14958S), pSer2 (1:900, Abcam, Ab5095), pSer5 (1:1000, Cell Signaling Technology, 13523S), CDK7 (1:1000, Abcam, ab256787), anti-CDK9 (1:1000, Cell Signaling Technologies, 2316), ANLN (1:500, Santa Cruz, sc-271814), anti-DDX21 (1:5000, ProteinTech, 10528-1-AP), NPM1 (1:1000, Abmart, PK66455S), INT4 (1:1000, ProteinTech, 16130-1-AP), INT11 (1:300, ProteinTech, 15860-1-AP; 1:5000, Bethyl Labs, A301-274A). Secondary antibodies used included goat anti-Rabbit IgG (H + L) secondary antibody-HRP (1:5000, Beijing Ray Antibody Biotech, RM3001) and goat anti-mouse IgG (H + L) secondary antibody-HRP (1:5000, Beijing Ray Antibody Biotech, RM3002). Protein bands were detected with an enhanced chemiluminescence (ECL) kit and imaged by Tanon 4600SF Imaging System. Cell proliferation assay 1.5×10 5 cells were seeded in a 6-well plate. After culturing for 24 hours, cells were treated with DMSO or 500 nM dTAG-13 (Sigma-Aldrich, SML2601), and counted every 24 hours for 3 consecutive days by Invitrogen Countess 3. Analysis of apoptosis Cell apoptosis analysis using Annexin V-PE Apoptosis Detection Kit (Keygen Biotech, KGA1030) in accordance to manufacturer’s instructions. Briefly, cells were washed with PBS and dissociated by treatment with trypsin-EDTA. Single cell suspension was washed twice with PBS/2% BSA, and 1 ~ 5×10 5 cells were resuspended in 500 µL of Binding Buffer. 5 µL of FITC-Annexin V and PI were added and cells were incubated at room temperature for 5 ~ 10 mins in dark. Cells were left on ice and subjected to flow cytometry analysis within 1 hour on the BD FACSAria Fusion cell sorter. Data were acquired and analyzed using FlowJo version 10.8.1 software. Cell cycle analysis Cell cycle was detected with propidium iodide and a cell cycle detection kit (Keygen Biotech, KGA512) according to the manufacturer’s protocols. Briefly, cells were washed with PBS and dissociated by treatment with trypsin-EDTA. 1.5×10 6 cells were fixed overnight at 4°C with 70% cold ethanol. Before staining, cells were with PBS, and then incubated with 500 µL of the pre-prepared PI/RNase A staining working solution in the dark at room temperature for 30 ~ 60 mins. Cells were detected on the BD FACSAria Fusion cell sorter, and the red fluorescence was recorded at an excitation wavelength of 488 nm. Data were acquired and analyzed using FlowJo version 10.8.1 software. Immunoprecipitation and Mass spectrometry mESCs were lysed in lysis buffer (20 mM HEPES pH 7.4, 140 mM NaCl, 2 mM MgCl 2 , 10% glycerol, 0.5% NP-40, 0.2 mM EDTA, 2 mM dithiothreitol (DTT), and 1× protease inhibitor) for 30 mins on ice. The lysate was centrifuged at 20,000 g for 30 mins at 4°C and the supernatant was collected and incubated with anti-HA Magnetic beads (MedChemExpress, HY-K0201) for 2 hours at 4°C. For Co-Immunoprecipitation (Co-IP), 2 µg INTS4 (ProteinTech, 16130-1-AP) or INTS11 (Bethyl Labs, A301-274A) antibodies overnight at 4°C. Pierce™ Protein A/G Magnetic Beads (Thermo, 88802) were washed three times with beads wash buffer (50 mM Tris-HCl, 150 mM NaCl, 0.5% Tween-20 pH 7.4). Pre-washed magnetic beads were added to the cells with gentle vortexing. Samples were incubated at room temperature with mixing for 1 hour. Beads were collected with a magnetic stand and washed three times with lysis buffer and twice with wash buffer. After washing five times as above, SDS loading buffer (100 mM Tris pH 7.5, 4%SDS, 10 mM DTT) was directly mixed with the beads. Supernatant was mixed with 5× loading buffer, and heated at 95°C for 10 mins for western blotting detection. For mass spectrometry, proteins were immunoprecipitated with anti-HA Magnetic beads. After washing five times, SDS loading buffer (100 mM Tris pH 7.5, 4% SDS, 10 mM DTT) was directly mixed with the beads for western blotting detection and proteins were cut from gels for mass spectrometry. the gel containing proteins was cut into pieces and de-stain in 25 mM ammonium bicarbonate/50% acetonitrile buffer. After decolored, the proteins were reduced with 10 mM DTT in 50 mM ammonium bicarbonate at 56 ℃ for 1 hour and alkylated with 55 mM iodoacetamide in 50 mM ammonium bicarbonate in the dark for 45 mins, and digested with trypsin at 37 ℃ overnight. Peptides were extracted from gel with buffers containing 5% trifluoroacetic acid and 50% acetonitirile by ultrasonic twice. The liquid was freeze dried by SpeedVac, and peptides were desalted by StageTip. LC-MS/MS analysis and Protein Identification Peptides were resuspended in 0.1% FA and analyzed by LTQ Orbitrap Elite mass spectrometer (ThermoFisher Scientific) coupled online to an Easy-nLC 1000 (Thermo Fisher Scientific) in the data-dependent mode. The peptides were separated by reverse phase LC with an 150 µm (ID) ×250 mm (length) analytical column packed with C18 particles of 1.9 µm diameter. The mobile phases for the LC contains buffer A (0.1% FA ) and buffer B (100% ACN, 0.1% FA), and a non-linear gradient of buffer B from 3%-30% for 90 min was used for the separation. Precursor ions were measured in the Orbitrap analyzer at 240,000 resolution (at 400 m/z) and a target value of 10^ 6 ions. The tweenty most intense ions from each MS scan were isolated, fragmented, and measured in the linear ion trap. The CID normalized collision energy was set to 35. The database search was performed for all raw MS files using the software MaxQuant (version 2.3.1.0). The Mus musculus proteome sequence database (21701 entries) from UniProt was applied to searching the data. The parameters used for the database search were set up as follows: Type: standard; Multiplicity: 1; The protease used for protein digestion: trypsin; Label free quantification: LFQ; The minimum score for unmodified peptides: 15. Default values were used for all other parameters. ATAC-seq ATAC–seq was performed as previously described with modification(Zhang et al., 2020 ). Briefly, mESCs cells were digested with adapter-loaded Tn5 (Vazyme, S604-01) in the tagmentation buffer (33 mM Tris-Acetate, 66 mM K-Acetate, 10 mM Mg-Acetate,16% DMF, 0.02% Digitonin) for 30 mins at 37°C, and the reaction was stopped by stop buffer (100 mM Tris pH 8.0, 100 mM NaCl, 0.4% SDS and 40 µg/mL Proteinase K) and incubated overnight at 55°C. 25% Tween-20 was added to quench SDS. Sequencing libraries were prepared with NEBNext High-Fidelity 2× PCR Master Mix. The PCR product was purified using a 1:1.6 volume ratio of SPRI beads. After 10 mins incubation at RT the beads were washed twice with 180 ~ 200 µL 80% freshly-prepared ethanol on the magnetic stand and the dried beads pellets were resuspended in 20µL RNAse free water. Libraries were quantified by Equalbit 1× dsDNA HS Assay Kit (Vazyme, EQ121-02) and quality was checked using Fragment Analyzer 12 with DNF-474-0500 HS NGS Fragment Kit (Agilent, 9994). SLAM-seq SLAM-seq was performed as previously described with modifications. mESCs were cultured with culture medium containing 500 µM 4-thiouridine (4sU) for 1 or 2 hours to metabolically label newly synthesized RNA. Cells were detached using Trypsin/EDTA and washed twice in cold PBS after centrifugation at 600×g and finally resuspended in cold PBS. 6×10 4 cells were lysed in 10µL lysis buffer (10 mM Tris-HCl pH 7.5, 10 mM NaCl, 3 mM MgCl, 2 U/µl RNase inhibitor, 0.02% Digitonin), and incubated at room temperature for at least 3mins, then put on ice. After frozen on dry ice, the lysate was thawed at room temperature for 3-5mins. Total RNA was thiol-linked alkylated by iodoacetamide (IAA) for 15 mins at 50°C in a mixture containing 10 mM IAA, 1x PBS, and 50% DMSO. Alkylation was stopped by adding DTT to 15 mM. The 4sU-labeled RNA was isolated using a 1:1 volume of RNA XP magnetic beads. After 10 mins incubation at room temperature, the beads were washed twice with 180 ~ 200 µL 80% freshly-prepared ethanol on the magnetic stand and the dried beads pellets were resuspended in 7 µL RNAse free water. 1 µL of 10 µM Oligo-dT primer and 1 µL of 10 mM dNTP were added into the 4sU-labeled RNA. After incubation at 72°C for 3 mins, and samples were placed on ice for 2 mins. 9.5 µL of the Reverse Transcription Mix containing 0.5 µL of 40 U/µL RNase Inhibitor and 1 µL of 200 U/µL SuperScript II Reverse Transcriptase were added for reverse transcription. The reaction was performed according to the manual using the following PCR conditions: 42°C for 90 mins; thermocycling for 10 cycles at 50°C for 2 mins, 42°C for 2 mins; followed by 70°C for 15 mins; and holding at 4°C. Amplification was performed by adding 25 µL of 2× KAPA HiFi Master Mix, 4.5 µL of Nuclease-free water and 0.5 µL of 10 µM ISPCR primer mix into the first-strand reaction sample. After PCR amplification, cDNAs were isolated using a 1:1.1 volume of SPRI beads. Libraries were quantified by Equalbit 1× dsDNA HS Assay Kit (Vazyme, EQ121-02) and quality was checked using Fragment Analyzer12 with DNF-474-0500 HS NGS Fragment Kit (Agilent, 9994) . Cleavage under targets and tagmentation (CUT&Tag) assay The CUT&Tag assay was performed as previously described with modifications(Kaya-Okur et al., 2019 ), using the Hyperactive Universal CUT&Tag Assay Kit for Illumina (Vazyme Biotech, TD903). Briefly, mESCs cells were washed with 500 µL wash buffer and centrifuged at 600× g for 5 mins at room temperature. 1× 10 5 cells were captured with concanavalin A-coated magnetic beads. The bead-bound cells were resuspended with 50 µL antibody buffer containing rabbit anti-pSer2 (1:50, Abcam, Ab5095), pSer5 (1:50, Cell Signaling Technology, 13523S), H3K4me3 (1:50, Active Motif, 39016), H3K27ac (1:50, Active Motif, 39034). After incubation overnight at 4°C, the primary antibody was carefully discarded and 0.5 µL Goat Anti-Rabbit IgG H&L (1:100, Vazyme, Ab207-01) diluted with 50 µL Dig-wash buffer was added to the cells. The cells were then incubated with rotation at room temperature for 1 hour. After washing gently with 200 µL Dig-wash buffer, 2 µL pA/G–Tnp together with 98 µl Dig-300 buffer was added to the samples. After incubating at room temperature for 1 hour, the samples were washed gently with 200 µL Dig-300 buffer. Then, 10 µL 5× TTBL mixed with 40 µL Dig-300 buffer was added to each sample and incubated at 37°C for 1 hour. The reactions were stopped by adding 5 µL 20 mg/ml Proteinase K, 100 µL Buffer L/B, and 20 µL DNA extraction beads and incubating at 55°C for 10 mins. The supernatant was discarded and the beads were washed once with 200 µL Buffer WA and twice with 200 µL Buffer WB and resuspended with 21 µL nuclease free water. For library amplification, 20 µL of purified DNA was mixed with 25 µL of 2× CAM, along with 2.5 µL of uniquely barcoded i5 and i7 primers. A total volume of 50 µL of sample was placed in a PCR thermal cycler using the following program: 72°C for 3 mins; 98°C for 3 mins; thermocycling for 11 cycles at 98°C for 10 secs, 60°C for 5 secs, followed by 72°C for 1 mins; and holding at 4°C. PCR products were purified with SPRI beads. All libraries were sequenced by Novogene using the Illumina NovaSeq 6000 platform in PE150 mode (Novogene, Beijing, China). Statistics Significant differences between groups (DMSO vs dTAG) were tested using GraphPad Prism (GraphPad Software Version 10.4.1). The number of samples used per experiment is presented in figures or figure legends. Tests used to calculate statistical significance are mentioned in figure legends. All data are presented as means ± SDs. A P value of 0.05 was considered statistically significant. In the histogram and curve, P *<0.05, P **<0.01, P ***<0.001, P ****<0.0001, and ns (not significant) are indicated. CoIP-MS data analysis Raw acquisition files of the proteome samples were analyzed together with MaxQuant (v2.3)(Cox and Mann, 2008 ). Then, the proteinGroups.txt result tables were analyzed and visualized with R package DEP2 (v0.5.28.2)(Zhang et al., 2018a ). Data was filtered by missing value, normalized using vsn and imputed. Proteins were considered differentially enriched when the fold change was greater than 2, and the P value was lower than 0.05. The volcano plot was generated in ggplot2 (v3.5.1). RNA-seq data analysis The raw paired-end RNA-seq reads were trimmed with Trim Galore (v0.6.7) ( https://www.bioinformatics.babraham.ac.uk/projects/trim_galore ). Then, the cleaned reads were mapped to the GRCm39 genome by STAR (v2.7.11a)(Dobin et al., 2013 ) and the gene annotation file was downloaded from GENECODE (vM32)(Frankish et al., 2023 ). RSEM (v1.3.1)(Li and Dewey, 2011 ) was used to calculate gene expression levels and DESeq2 (v1.44.0)(Love et al., 2014 ) was applied to identify differentially expressed genes. The significantly differentially expressed genes were called with an adjusted P value cut-off of 0.05 and a fold change cut-off of 2. Gene ontology (GO) analysis was performed using R package clusterProfiler (v4.12.6)(Yu et al., 2012 ) and enrichplot (v1.24.2) ( https://github.com/YuLab-SMU/enrichplot ). SLAM-seq data analysis Adapters were trimmed from raw reads using Cutadapt (v3.5) through the Trim Galore (v0.6.7) ( https://www.bioinformatics.babraham.ac.uk/projects/trim_galore ) wrapper tool. SLAM-seq analyses were performed using the SLAMdunk pipeline (v0.4.3)(Neumann et al., 2019 ), which includes mapping, read filtering, single-nucleotide polymorphism (SNP) variant calling, conversion counts and rate calculation. MultiQC and separate BAM files for labeled and unlabeled reads using the Alleyoop collapse program from SlamDunk. The significantly differentially expressed genes were called using DESeq2 (v1.44.0)(Love et al., 2014 ) with size factors estimated on corresponding total mRNA reads for global normalization with an adjusted P value cut-off of 0.05 and fold change cut-off of 2. GO analysis was performed similarly to RNA-seq. ATAC-seq and CUT&Tag data analysis The paired-end raw reads were first trimmed of the adaptors with Trim Galore (v0.6.7) ( https://www.bioinformatics.babraham.ac.uk/projects/trim_galore ) and then aligned to the GRCm39 genomes using Bowtie2 (v2.4.4)(Langmead and Salzberg, 2012 ) with the following parameters: --no-unal --no-mixed --no-discordant. Low mapping quality reads (MAPQ < 30), unmapped reads and duplicated reads were removed using Sambamba (v1.0.1)(Tarasov et al., 2015 ), Picard (v2.21.4) ( https://broadinstitute.github.io/picard/ ) and SAMtools (v1.13)(Li et al., 2009 ). For the histone modification CUT&Tag, the mapped reads were further filtered to retain only proper paired reads with fragment length at least 178bp. Read coverages over the genome were estimated by bamCoverage from deepTools (v3.5.1)(Ramirez et al., 2016 ) with the following parameters: --binSize 20 --minMappingQuality 30 --scaleFactor 1 --normalizeUsing RPKM, and visualized by Integrative Genomics Viewer (IGV) (v2.16.2)(Thorvaldsdottir et al., 2013 ). Motif enrichment analysis The motif files were acquired from the JASPAR database(Rauluseviciute et al., 2024 ) and converted to HOMER motif format by dumpJaspar with R package monaLisa (v1.11.1)(Machlab et al., 2022 ). The locations of GABPA motifs in the genome-wide were determined using scanMotifGenomeWide.pl from HOMER (v5.0.1)(Heinz et al., 2010 ), and the quantity of motifs present in the promoters was assessed by overlapping them with genome-wide motif locations. The JASPAR motif IDs for GABPA is MA0062.2. Data availability All data generated in this study have been deposited to the NCBI Gene Expression Omnibus (GEO) with accession number GSE304514 (Token for reviewers’ access: qlufeasmznqpbgf). Mouse oocyte to eight-cell and E3.5 ICM RNA-seq data from GSE71434(Zhang et al., 2016 ) and GSE76505(Zhang et al., 2018b ), respectively. GABPA CUT&RUN data from GSE263171(Zhou et al., 2025 ). INTS11 ChIP-seq and SLAM-seq from GSE181714(Wang et al., 2023 ). Declarations Data availability All data generated in this study have been deposited to the NCBI Gene Expression Omnibus (GEO) with accession number GSE304514 (Token for reviewers’ access: qlufeasmznqpbgf). Mouse oocyte to eight-cell and E3.5 ICM RNA-seq data from GSE71434(Zhang et al., 2016) and GSE76505(Zhang et al., 2018b), respectively. GABPA CUT&RUN data from GSE263171(Zhou et al., 2025). INTS11 ChIP-seq and SLAM-seq from GSE181714(Wang et al., 2023). Acknowledgements We thank Dr. Jingsi Tang for her valuable discussions on the project and comments on the manuscript. This project was supported by the National Natural Science Foundation of China (32370865). We thank Professor Yingchun Wang and Dr. Xiahe Huang (the Institute of Genetics and Developmental Biology of the Chinese Academy of Sciences) for providing technical support for mass spectrometry. We thank Ting Li (the Institute of Genetics and Developmental Biology of the Chinese Academy of Sciences) for her excellent technical assistance in flow cytometry. Author contributions C-X.Z. conceived and supervised the project. H.Y. performed all the bioinformatic analysis. J-J.G. established GABPB1-dTAG and GABPB1/B2-dTAG ESCs, and performed the experiments including RNA-seq, SLAM-seq, CoIP-MS, ATAC-seq etc. B-Q.W. performed the CUT&Tag. H.Y., J-J.G and C-X.Z. wrote the manuscript. All authors interpreted the data and reviewed the manuscript. Competing interests The authors declare no competing interests. References Abuhashem A, Lee AS, Joyner AL, Hadjantonakis AK (2022) Rapid and efficient degradation of endogenous proteins in vivo identifies stage-specific roles of RNA Pol II pausing in mammalian development. Dev Cell 57:1068–1080e1066 Aoi Y, Takahashi YH, Shah AP, Iwanaszko M, Rendleman EJ, Khan NH, Cho BK, Goo YA, Ganesan S, Kelleher NL et al (2021) SPT5 stabilization of promoter-proximal RNA polymerase II. Mol Cell 81:4413–4424e4415 Bush TS, St Coeur M, Resendes KK, Rosmarin AG (2003) GA-binding protein (GABP) and Sp1 are required, along with retinoid receptors, to mediate retinoic acid responsiveness of CD18 (beta 2 leukocyte integrin): a novel mechanism of transcriptional regulation in myeloid cells. Blood 101:311–317 Cox J, Mann M (2008) MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification. Nat Biotechnol 26:1367–1372 Dobin A, Davis CA, Schlesinger F, Drenkow J, Zaleski C, Jha S, Batut P, Chaisson M, Gingeras TR (2013) STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29:15–21 Elrod ND, Henriques T, Huang KL, Tatomer DC, Wilusz JE, Wagner EJ, Adelman K (2019) The Integrator Complex Attenuates Promoter-Proximal Transcription at Protein-Coding Genes. Mol Cell 76:738–752e737 Frankish A, Carbonell-Sala S, Diekhans M, Jungreis I, Loveland JE, Mudge JM, Sisu C, Wright JC, Arnan C, Barnes I et al (2023) GENCODE: reference annotation for the human and mouse genomes in 2023. Nucleic Acids Res 51:D942–D949 Heinz S, Benner C, Spann N, Bertolino E, Lin YC, Laslo P, Cheng JX, Murre C, Singh H, Glass CK (2010) Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities. Mol Cell 38:576–589 Hu S, Peng L, Song A, Ji YX, Cheng J, Wang M, Chen FX (2023) INTAC endonuclease and phosphatase modules differentially regulate transcription by RNA polymerase II. Mol Cell 83:1588–1604e1585 Hu S, Peng L, Xu C, Wang Z, Song A, Chen FX (2021) SPT5 stabilizes RNA polymerase II, orchestrates transcription cycles, and maintains the enhancer landscape. Mol Cell 81:4425–4439e4426 Isbel L, Grand RS, Schubeler D (2022) Generating specificity in genome regulation through transcription factor sensitivity to chromatin. Nat Rev Genet 23:728–740 Kaya-Okur HS, Wu SJ, Codomo CA, Pledger ES, Bryson TD, Henikoff JG, Ahmad K, Henikoff S (2019) CUT&Tag for efficient epigenomic profiling of small samples and single cells. Nat Commun 10 , 1930 Krueger BJ, Jeronimo C, Roy BB, Bouchard A, Barrandon C, Byers SA, Searcey CE, Cooper JJ, Bensaude O, Cohen EA et al (2008) LARP7 is a stable component of the 7SK snRNP while P-TEFb, HEXIM1 and hnRNP A1 are reversibly associated. Nucleic Acids Res 36:2219–2229 Lambert SA, Jolma A, Campitelli LF, Das PK, Yin Y, Albu M, Chen X, Taipale J, Hughes TR, Weirauch MT (2018) Hum Transcription Factors Cell 172:650–665 Langmead B, Salzberg SL (2012) Fast gapped-read alignment with Bowtie 2. Nat Methods 9:357–359 Li B, Dewey CN (2011) RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinformatics 12:323 Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, Marth G, Abecasis G, Durbin R (2009) The Sequence Alignment/Map format and SAMtools, vol 25. Bioinformatics, pp 2078–2079. and Genome Project Data Processing Love MI, Huber W, Anders S (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15:550 Machlab D, Burger L, Soneson C, Rijli FM, Schubeler D, Stadler MB (2022) monaLisa: an R/Bioconductor package for identifying regulatory motifs. Bioinformatics 38:2624–2625 Nabet B, Roberts JM, Buckley DL, Paulk J, Dastjerdi S, Yang A, Leggett AL, Erb MA, Lawlor MA, Souza A et al (2018) The dTAG system for immediate and target-specific protein degradation. Nat Chem Biol 14:431–441 Neumann T, Herzog VA, Muhar M, von Haeseler A, Zuber J, Ameres SL, Rescheneder P (2019) Quantification of experimentally induced nucleotide conversions in high-throughput sequencing datasets. BMC Bioinformatics 20:258 Nishimura K, Fukagawa T, Takisawa H, Kakimoto T, Kanemaki M (2009) An auxin-based degron system for the rapid depletion of proteins in nonplant cells. Nat Methods 6:917–922 Ramirez F, Ryan DP, Gruning B, Bhardwaj V, Kilpert F, Richter AS, Heyne S, Dundar F, Manke T (2016) deepTools2: a next generation web server for deep-sequencing data analysis. Nucleic Acids Res 44:W160–165 Rauluseviciute I, Riudavets-Puig R, Blanc-Mathieu R, Castro-Mondragon JA, Ferenc K, Kumar V, Lemma RB, Lucas J, Cheneby J, Baranasic D et al (2024) JASPAR 2024: 20th anniversary of the open-access database of transcription factor binding profiles. Nucleic Acids Res 52:D174–D182 Razew M, Fraudeau A, Pfleiderer MM, Linares R, Galej WP (2024) Structural basis of the Integrator complex assembly and association with transcription factors. Mol Cell 84:2542–2552e2545 Reiff RE, Ali BR, Baron B, Yu TW, Ben-Salem S, Coulter ME, Schubert CR, Hill RS, Akawi NA, Al-Younes B et al (2014) METTL23, a transcriptional partner of GABPA, is essential for human cognition. Hum Mol Genet 23:3456–3466 Resendes KK, Rosmarin AG (2006) GA-binding protein and p300 are essential components of a retinoic acid-induced enhanceosome in myeloid cells. Mol Cell Biol 26:3060–3070 Sawada J, Simizu N, Suzuki F, Sawa C, Goto M, Hasegawa M, Imai T, Watanabe H, Handa H (1999) Synergistic transcriptional activation by hGABP and select members of the activation transcription factor/cAMP response element-binding protein family. J Biol Chem 274:35475–35482 Sharrocks AD (2001) The ETS-domain transcription factor family. Nat Rev Mol Cell Biol 2:827–837 Soto LF, Li Z, Santoso CS, Berenson A, Ho I, Shen VX, Yuan S, Bass F, J.I (2022) Compendium of human transcription factor effector domains. Mol Cell 82:514–526 Spitz F, Furlong EE (2012) Transcription factors: from enhancer binding to developmental control. Nat Rev Genet 13:613–626 Stadhouders R, Filion GJ, Graf T (2019) Transcription factors and 3D genome conformation in cell-fate decisions. Nature 569:345–354 Takahashi K, Tanabe K, Ohnuki M, Narita M, Ichisaka T, Tomoda K, Yamanaka S (2007) Induction of pluripotent stem cells from adult human fibroblasts by defined factors. Cell 131:861–872 Tarasov A, Vilella AJ, Cuppen E, Nijman IJ, Prins P (2015) Sambamba: fast processing of NGS alignment formats. Bioinf 31, 2032–2034 Thompson CC, Brown TA, McKnight SL (1991) Convergence of Ets- and notch-related structural motifs in a heteromeric DNA binding complex. Science 253:762–768 Thorvaldsdottir H, Robinson JT, Mesirov JP (2013) Integrative Genomics Viewer (IGV): high-performance genomics data visualization and exploration. Brief Bioinform 14:178–192 Ueda A, Akagi T, Yokota T (2017) GA-Binding Protein Alpha Is Involved in the Survival of Mouse Embryonic Stem Cells. Stem Cells 35:2229–2238 Wang H, Fan Z, Shliaha PV, Miele M, Hendrickson RC, Jiang X, Helin K (2023) H3K4me3 regulates RNA polymerase II promoter-proximal pause-release. Nature 615:339–348 Yu G, Wang LG, Han Y, He QY (2012) clusterProfiler: an R package for comparing biological themes among gene clusters. Omics 16:284–287 Zhang B, Zheng H, Huang B, Li W, Xiang Y, Peng X, Ming J, Wu X, Zhang Y, Xu Q et al (2016) Allelic reprogramming of the histone modification H3K4me3 in early mammalian development. Nature 537:553–557 Zhang C, Chen Z, Yin Q, Fu X, Li Y, Stopka T, Skoultchi AI, Zhang Y (2020) The chromatin remodeler Snf2h is essential for oocyte meiotic cell cycle progression. Genes Dev 34:166–178 Zhang X, Smits AH, van Tilburg GB, Ovaa H, Huber W, Vermeulen M (2018a) Proteome-wide identification of ubiquitin interactions using UbIA-MS. Nat Protoc 13:530–550 Zhang Y, Xiang Y, Yin Q, Du Z, Peng X, Wang Q, Fidalgo M, Xia W, Li Y, Zhao ZA et al (2018b) Dynamic epigenomic landscapes during early lineage specification in mouse embryos. Nat Genet 50:96–105 Zheng H, Qi Y, Hu S, Cao X, Xu C, Yin Z, Chen X, Li Y, Liu W, Li J et al (2020) Identification of Integrator-PP2A complex (INTAC), an RNA polymerase II phosphatase. Sci 370 Zhou C, Wang M, Zhang C, Zhang Y (2025) The transcription factor GABPA is a master regulator of naive pluripotency. Nat Cell Biol 27:48–58 Additional Declarations There is NO Competing Interest. Supplementary Files Yangeta.2025TableS1.xlsx Supplementary Table 1 Yangeta.2025TableS2.xlsx Supplementary Table 2 Yangeta.2025TableS3.xlsx Supplementary Table 3 Yangeta.2025TableS4.xlsx Supplementary Table 4 Supplementaryfigurelegends.docx Cite Share Download PDF Status: Under Review Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7297262","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":517199420,"identity":"7aa8fb67-7e02-46f1-8276-808e0712c9a1","order_by":0,"name":"Chunxia Zhang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9UlEQVRIiWNgGAWjYHACNhAhB2EbkKDFGMw8QIqWxAawFmLU889If/bg547a9PnuvQcffyiws2dgP/yA4ecO3FokzhxIN+w9czx345lzyQYHDJITG3jSDBh7z+DWYsDecEyCt+1Y7sYZOWYSBwwOJDAw5DAwM7bh0QKUlfzbdizdcP4b8x9ALfYM/G8IaGFvZpPmbatJkJfgMQOG2AHGBgkCtkicOcYmLdt2wHADT46xxBmgX9oknhkc7MWjBRRikm/b6uTl288Yfqj4Y2fPz5/88MFPPFqg4DCDwQEoExRNB3CrhIM6BvkGIpSNglEwCkbByAQA1lhPDkD9GncAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0003-0063-9181","institution":"Institute of Genetics and Developmental Biology, Chinese Academy of Sciences","correspondingAuthor":true,"prefix":"","firstName":"Chunxia","middleName":"","lastName":"Zhang","suffix":""},{"id":517199421,"identity":"a09ad704-d61c-47ba-82ee-d2a77a43a6a3","order_by":1,"name":"Hang Yang","email":"","orcid":"","institution":"Institute of Genetics and Developmental Biology, Chinese Academy of Sciences","correspondingAuthor":false,"prefix":"","firstName":"Hang","middleName":"","lastName":"Yang","suffix":""},{"id":517199422,"identity":"292ac479-2deb-4259-a205-f59569c10151","order_by":2,"name":"Jinjing Geng","email":"","orcid":"","institution":"Institute of Genetics and Developmental Biology, Chinese Academy of Sciences","correspondingAuthor":false,"prefix":"","firstName":"Jinjing","middleName":"","lastName":"Geng","suffix":""},{"id":517199423,"identity":"ada6cbc2-ccfd-462f-9689-b2811e9f951c","order_by":3,"name":"Wusa Baqie","email":"","orcid":"","institution":"Institute of Genetics and Developmental Biology, Chinese Academy of Sciences","correspondingAuthor":false,"prefix":"","firstName":"Wusa","middleName":"","lastName":"Baqie","suffix":""}],"badges":[],"createdAt":"2025-08-05 07:00:15","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7297262/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7297262/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":91817077,"identity":"3a98dc03-b71e-4cc4-82ec-4932e1858686","added_by":"auto","created_at":"2025-09-22 06:53:32","extension":"xlsx","order_by":5,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":11730,"visible":true,"origin":"","legend":"","description":"","filename":"Yangeta.2025TableS4.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7297262/v1/b0b53164562426a9138d01a0.xlsx"},{"id":91690561,"identity":"56558a49-f30d-4b2f-8600-95a85d3cdefa","added_by":"auto","created_at":"2025-09-19 08:36:20","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":273021,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGABPA regulates mESC survival in a GABPB1/B2-independent way\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Brightfield images showing conversion of \u003cem\u003eGabpa\u003c/em\u003e\u003csup\u003edTAG/dTAG\u003c/sup\u003e,\u003cem\u003e Gabpb1\u003c/em\u003e\u003csup\u003edTAG/dTAG\u003c/sup\u003e,\u003cem\u003e \u003c/em\u003eand\u003cem\u003e Gabpb1/b2\u003c/em\u003e\u003csup\u003edTAG/dTAG\u003c/sup\u003e mESCs treated with DMSO or 500 nM dTAG13 for 12 hours. Scale bar, 200 μm.\u003c/p\u003e\n\u003cp\u003e(B) Proliferation curves of mESCs treated with DMSO or 500 nM dTAG13 for the indicated genotypes (\u003cem\u003eGabpa\u003c/em\u003e\u003csup\u003edTAG/dTAG\u003c/sup\u003e\u003cem\u003e, Gabpb1\u003c/em\u003e\u003csup\u003edTAG/dTAG\u003c/sup\u003e\u003cem\u003e, \u003c/em\u003eand\u003cem\u003e Gabpb1/b2\u003c/em\u003e\u003csup\u003edTAG/dTAG\u003c/sup\u003e). Significant differences between dTAG and DMSO were tested using\u0026nbsp;a two-way ANOVA with multiple comparisons of GraphPad Prism. The data are presented as the mean ± SD (n = 3).\u003c/p\u003e\n\u003cp\u003e(C-E) Differentially expressed genes in RNA-seq after GABPA (C), GABPB1 (D) and GABPB1\u0026amp;B2 (E) depletion for 12 hours, with significantly up- and down-regulated genes (fold change ≥ 2 and adjusted \u003cem\u003eP\u003c/em\u003e value \u0026lt; 0.05) in red and blue dots, respectively.\u003c/p\u003e\n\u003cp\u003e(F) Venn diagram showing the overlapping significant down-regulated genes after GABPA, GABPB1 and GABPB1\u0026amp;B2 depletion for 12 hours.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7297262/v1/84fb754e0b9db8288ae51099.png"},{"id":91690562,"identity":"4c457c94-e3a9-4981-84f0-827baffa8e10","added_by":"auto","created_at":"2025-09-19 08:36:20","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":321180,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGABPA interacts with core transcriptional machinery in mESCs\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Volcano plot illustrating the proteins that interacted with GABPA using HA immunoprecipitation coupled with mass spectrometry (IP-MS).\u003c/p\u003e\n\u003cp\u003e(B) Proteins that interact with GABPA are associated with transcription regulation, chromatin organization, and epigenetic modification.\u003c/p\u003e\n\u003cp\u003e(C) Co-immunoprecipitation (Co-IP) analyses of GABPA-HA with RNA polymerase II (Pol II), Pol II phosphorylated at Ser5 (pSer5) or Ser2 (pSer2), INTS4 and INTS11 (integrator complex subunits) in \u003cem\u003eGabpa\u003c/em\u003e\u003csup\u003edTAG/dTAG\u003c/sup\u003e mESCs after GABPA depletion for 12 hours. Input and IgG controls are shown.\u003c/p\u003e\n\u003cp\u003e(D) Co-IP analyses of endogenous INTS4 and INTS11 with GABPA-HA. Input and IgG controls are shown.\u003c/p\u003e\n\u003cp\u003e(E) Enrichment of GABPA CUT\u0026amp;RUN and INTS11 ChIP-seq signals around the TSS region (TSS ± 2 kb) of GABPA-bound and unbound genes. RPKM, reads per kilobase million.\u003c/p\u003e\n\u003cp\u003e(F) Enrichment of \u003cem\u003ede novo\u003c/em\u003e TF motifs at the INTS11 peaks.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7297262/v1/423da19e3fdec5e396c0c965.png"},{"id":91690563,"identity":"8ae46880-5fcf-400c-b718-9b9ae3f27995","added_by":"auto","created_at":"2025-09-19 08:36:20","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":538173,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGABPA recruits INTS4/9/11 complex to regulate the expression of ribosome biogenesis related genes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Volcano plot depicting changes in nascent transcription (SLAM-seq) following GABPA degradation for 12 hours, with significantly up- and down-regulated genes (fold change ≥ 2 and adjusted \u003cem\u003eP\u003c/em\u003e value \u0026lt; 0.05) in red and blue dots, respectively.\u003c/p\u003e\n\u003cp\u003e(B) Gene ontology (GO) enrichment analysis of significantly down- and up-regulated genes in (A), represented by blue and pink bars, respectively. The enriched terms are ranked by -log\u003csub\u003e10\u003c/sub\u003e(adjusted \u003cem\u003eP\u003c/em\u003e value).\u003c/p\u003e\n\u003cp\u003e(C) Heatmaps showing the DEGs in mESCs upon GABPA depletion for 12 hours and the GABPA CUT\u0026amp;RUN signals around the TSS region (TSS ± 2 kb) of corresponding genes. CR, CUT\u0026amp;RUN. FC, fold change.\u003c/p\u003e\n\u003cp\u003e(D) Venn diagram showing the overlaps of down-regulated, up-regulated, and GABPA-bound gene lists.\u003c/p\u003e\n\u003cp\u003e(E) Box plots showing the nascent transcriptional changes with the number of GABPA binding motifs at the promoter of genes. The central band represents the median, the lower and upper edges of the box represent the first and third quartiles, respectively. \u003cem\u003eP\u003c/em\u003e values were calculated using Wilcoxon tests.\u003c/p\u003e\n\u003cp\u003e(F) Venn diagram showing the overlaps of down-regulated genes after GABPA and INTS11 depletion.\u003c/p\u003e\n\u003cp\u003e(G) GO enrichment analysis of overlapping genes in (F). The enriched terms are ranked by -log\u003csub\u003e10\u003c/sub\u003e(adjusted \u003cem\u003eP\u003c/em\u003e value).\u003c/p\u003e\n\u003cp\u003e(H) The left heatmaps show the INTS11 CUT\u0026amp;Tag signals around the TSS of overlapping down-regulated genes. The right box plots show the RPKM quantification of relative genes. The central band represents the median, the lower and upper edges of the box represent the first and third quartiles, respectively. \u003cem\u003eP\u003c/em\u003e values were calculated using Wilcoxon tests.\u003c/p\u003e\n\u003cp\u003e(I) Examples of the genome browser view of SLAM-seq, GABPA CUT\u0026amp;RUN, and INTS11 CUT\u0026amp;Tag results in mESCs with DMSO and dTAG treatment for 12 hours.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7297262/v1/eaa5daaeeabab753dda3d60e.png"},{"id":91690566,"identity":"ea36f839-0eff-4632-b8d5-5f9afafb6953","added_by":"auto","created_at":"2025-09-19 08:36:20","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":268734,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe primary effects on transcription after GABPA depletion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A-C) Volcano plot depicting changes in nascent transcription (SLAM-seq) following GABPA degradation for 1 hour (A), 2 hours (B), and 4 hours (C), with significantly up- and down-regulated genes (fold change ≥ 2 and adjusted \u003cem\u003eP\u003c/em\u003e value \u0026lt; 0.05) in red and blue dots, respectively. Label genes possess over three GABPA binding motifs in their promoter region, exhibiting down-regulation at 1 hour and corresponding times.\u003c/p\u003e\n\u003cp\u003e(D) Venn diagram showing the overlaps of down-regulated genes after GABPA depletion for 1, 2, and 4 hours.\u003c/p\u003e\n\u003cp\u003e(E) Sankey diagram showing the differentially expressed genes following GABPA depletion for 1, 2, and 4 hours.\u003c/p\u003e\n\u003cp\u003e(F) GO enrichment analysis of down-regulated genes in SLAM-seq after GABPA depletion for 1 hour. The enriched terms are ranked by -log\u003csub\u003e10\u003c/sub\u003e(adjusted \u003cem\u003eP\u003c/em\u003e value).\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7297262/v1/91c67a9c160509f15246f8df.png"},{"id":91690564,"identity":"9993a106-f1a9-422c-ab47-19e13a025c98","added_by":"auto","created_at":"2025-09-19 08:36:20","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":481349,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAcute depletion of GABPA leads to blockage of RNA Pol II elongation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Heatmaps showing the nascent down-regulated genes after GABPA depletion for 1 hour, as well as the GABPA CUT\u0026amp;RUN and INTS11 CUT\u0026amp;Tag results around the TSS of related genes. CT, CUT\u0026amp;Tag.\u003c/p\u003e\n\u003cp\u003e(B) Metaplots showing the INTS11 CUT\u0026amp;Tag signals around the TSS of nascent down-regulated genes after GABPA depletion for 1 hour.\u003c/p\u003e\n\u003cp\u003e(C) Box plots showing the INTS11 CUT\u0026amp;Tag changes at the promoter of nascent down-regulated genes. The central band represents the median, the lower and upper edges of the box represent the first and third quartiles, respectively. \u003cem\u003eP\u003c/em\u003evalues were calculated using Wilcoxon tests.\u003c/p\u003e\n\u003cp\u003e(D) Examples of the genome browser view of SLAM-seq, GABPA CUT\u0026amp;RUN, and INTS11 CUT\u0026amp;Tag results in mESCs with DMSO and dTAG treatment for 1 hour.\u003c/p\u003e\n\u003cp\u003e(E) Heatmaps showing the pSer5 CUT\u0026amp;Tag results around the TSS of nascent down-regulated genes after GABPA depletion for 1 hour, and the pSer2 signals across all related genes. S, transcription start site. E, transcription end site.\u003c/p\u003e\n\u003cp\u003e(F) Box plots showing the pSer5 and pSer2 changes at the promoter and gene body of nascent down-regulated genes. The central band represents the median, the lower and upper edges of the box represent the first and third quartiles, respectively. \u003cem\u003eP\u003c/em\u003e values were calculated using Wilcoxon tests.\u003c/p\u003e\n\u003cp\u003e(G) Examples of the genome browser view of pSer5 and pSer2 CUT\u0026amp;Tag results in mESCs with DMSO and dTAG treatment for 1 hour.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-7297262/v1/a53c4382187ba19a50edbe61.png"},{"id":91690567,"identity":"c7e8fffa-d317-49d2-92dc-01b328ae9e6f","added_by":"auto","created_at":"2025-09-19 08:36:20","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":537207,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eProlonged GABPA depletion impairs chromatin accessibility and general transcription machinery\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Heatmaps showing the ATAC-seq, H3K4me3, H3K27ac and pSer5 CUT\u0026amp;Tag signals around the TSS, and pSer2 signals across all genes of nascent down-regulated genes with DMSO and dTAG treatment for 12 hours. FC, fold change. S, transcription start site. E, transcription end site.\u003c/p\u003e\n\u003cp\u003e(B) Box plots showing the ATAC-seq, H3K4me3, H3K27ac, pSer5 and pSer2 CUT\u0026amp;Tag changes at the promoter and gene body of nascent down-regulated genes. The central band represents the median, the lower and upper edges of the box represent the first and third quartiles, respectively. \u003cem\u003eP\u003c/em\u003e values were calculated using Wilcoxon tests.\u003c/p\u003e\n\u003cp\u003e(C) Examples of the genome browser view of SLAM-seq, GABPA CUT\u0026amp;RUN, ATAC-seq, H3K4me3, H3K27ac, pSer5 and pSer2 CUT\u0026amp;Tag results in mESCs with DMSO and dTAG treatment for 12 hours.\u003c/p\u003e\n\u003cp\u003e(D) Western blot of whole-cell extracts of \u003cem\u003eGabpa\u003c/em\u003e\u003csup\u003edTAG/dTAG\u003c/sup\u003e mESCs treated with DMSO or 500 nM dTAG13 for 12 hours.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-7297262/v1/c31f7e51574176027094aca8.png"},{"id":91690568,"identity":"34ad8790-1431-4385-8fac-c3233e964514","added_by":"auto","created_at":"2025-09-19 08:36:20","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":196329,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGABPA recruits INTAC to drive promoter-proximal termination and productive elongation at ribosome biogenesis related genes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA model illustrating that GABPA physically engages the INTS4/9/11 endonuclease module of the Integrator complex to facilitate RNA polymerase II promoter-proximal termination and productive transcription elongation at ribosome biogenesis genes in wild type mESCs.\u003c/p\u003e\n\u003cp\u003eUpon acute GABPA depletion, INTAC fails to mediate promoter-proximal termination, and a marked reduction of gene body-associated Ser2-phosphorylated Pol II, indicative of defective elongation, ultimately results in downregulation of ribosome biogenesis genes.\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-7297262/v1/15c3ae4241abd433aabc9e35.png"},{"id":91989821,"identity":"1e17454c-9a18-417c-93ce-278775254586","added_by":"auto","created_at":"2025-09-23 12:35:23","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3410170,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7297262/v1/ab3b41f0-7a84-4c7f-bde9-cb111df986f5.pdf"},{"id":91691533,"identity":"f746ab1c-15af-4b8a-98f1-eaea2715732d","added_by":"auto","created_at":"2025-09-19 08:44:21","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":2780312,"visible":true,"origin":"","legend":"Supplementary Table 1","description":"","filename":"Yangeta.2025TableS1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7297262/v1/852eb3607eafdcbc1068b64a.xlsx"},{"id":91691532,"identity":"4cea9964-6b6d-4f5c-970f-44433c84f94f","added_by":"auto","created_at":"2025-09-19 08:44:20","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":227736,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary Table 2\u003c/p\u003e","description":"","filename":"Yangeta.2025TableS2.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7297262/v1/3df4a3da97a8698cfb9b4ffe.xlsx"},{"id":91691538,"identity":"8fc52f2f-72b0-4c42-a204-0a412cc857bd","added_by":"auto","created_at":"2025-09-19 08:44:21","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":7660444,"visible":true,"origin":"","legend":"Supplementary Table 3","description":"","filename":"Yangeta.2025TableS3.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7297262/v1/718ef342c3c8fc00907835a6.xlsx"},{"id":91691803,"identity":"50cce80d-9332-4748-9fa9-6383330d7a81","added_by":"auto","created_at":"2025-09-19 08:52:21","extension":"xlsx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":11730,"visible":true,"origin":"","legend":"Supplementary Table 4","description":"","filename":"Yangeta.2025TableS4.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7297262/v1/7d56505bd3a21af8385faf3d.xlsx"},{"id":91989552,"identity":"5b149e13-9603-4e70-bd7a-3e84533501e2","added_by":"auto","created_at":"2025-09-23 12:27:17","extension":"docx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":1613505,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementaryfigurelegends.docx","url":"https://assets-eu.researchsquare.com/files/rs-7297262/v1/b13c971b2ec51036f1a3bb90.docx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"GABPA Recruits the Integrator Endonuclease Complex to Promote Transcription Elongation","fulltext":[{"header":"Introduction","content":"\u003cp\u003eTranscriptional regulation is a fundamental process that governs cell identity and function, enabling dynamic control of gene expression programs throughout development, homeostasis, and disease. This multilayered process involves the coordinated recruitment and activity of transcriptional machinery at gene promoters and enhancers, and spans distinct stages including transcription initiation, promoter-proximal pausing, productive elongation, and termination. Transcription factors (TFs) play central roles in orchestrating this process by reading genomic regulatory sequences and translating them into context-specific transcriptional outputs(Stadhouders et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Takahashi et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Most TFs are modular in structure, comprising a sequence-specific DNA-binding domain (DBD) and an effector domain (ED) responsible for modulating transcriptional activity(Lambert et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Soto et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Effector domains are commonly classified into activator domains (ADs), repressor domains (RDs), or bifunctional modules that mediate both functions. Through these domains, TFs engage cofactors, chromatin remodelers, histone-modifying enzymes, and the general transcription machinery to control RNA polymerase II (Pol II) recruitment, chromatin accessibility, and transcriptional output(Isbel et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Spitz and Furlong, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2012\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eGABPA (GA-binding protein alpha), a member of the ETS transcription factor family, binds to DNA via a conserved ETS domain and is broadly expressed across mammalian cell types(Sharrocks, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). Canonically, GABPA forms a heterotetramer with one of two transcriptionally active β-subunits, GABPB1 or GABPB2, which harbor transcriptional activation domains (TADs) that mediate cofactor interactions and gene activation(Thompson et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e1991\u003c/span\u003e). In addition to its canonical partners, GABPA has been shown to cooperate with various cofactors in a context-dependent manner. For example, in myeloid cells, GABPA recruits the retinoic acid receptor to target promoters via p300-dependent enhanceosome assembly(Resendes and Rosmarin, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). while in the brain, the methyltransferase METTL23 interacts with GABPA to regulate cognition-related gene expression(Reiff et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Moreover, \u003cem\u003ein vitro\u003c/em\u003e studies have demonstrated that GABPA physically bound to the DNA binding domain of ATF1, forming a ternary complex composed of ATF1, GABPA and GABPB(Sawada et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e1999\u003c/span\u003e). Despite these diverse interaction profiles, the molecular mechanism by which GABPA regulates transcription has remained poorly understood.\u003c/p\u003e\u003cp\u003eOur recent work identified GABPA as a key regulator of na\u0026iuml;ve pluripotency establishment in mouse embryonic stem cells (mESCs)(Zhou et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2025\u003c/span\u003e), raising new questions about its mechanism of action in this context. However, conventional genetic approaches such as gene deletion or RNA interference have limited temporal resolution, often confounding direct TF targets with secondary transcriptional and epigenetic responses that emerge over time. Acute protein degradation technologies, including the auxin-inducible degron (AID) system(Nishimura et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) and the degradation tag (dTAG) system (Abuhashem et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Nabet et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), provide a powerful alternative by enabling rapid and selective depletion of proteins, thereby allowing interrogation of immediate and primary regulatory events.\u003c/p\u003e\u003cp\u003eIn this study, we applied the dTAG system to acutely degrade GABPA in mESCs and performed time-resolved transcriptomic and chromatin profiling to define its direct transcriptional roles. Strikingly, we uncovered a non-canonical function of GABPA in promoting transcriptional elongation independent of GABPB1/B2. Mechanistically, we show that GABPA physically associates with the Integrator complex, specifically its catalytic endonuclease module (INTS4/9/11), and facilitates its recruitment to promoter-proximal regions of GABPA target genes. Acute GABPA depletion led to a rapid and selective loss of Pol II Ser2 phosphorylation within gene bodies, consistent with defective pause-release and elongation. These findings position GABPA as an essential scaffold linking sequence-specific transcriptional targeting to the elongation machinery, thereby extending the functional repertoire of ETS family TFs. More broadly, this study illustrates how TFs can regulate gene expression through elongation-phase mechanisms that are independent of chromatin accessibility or initiation control, offering new insight into the principles of transcriptional regulation in mammalian stem cells.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eGABPA regulates mESC survival in a GABPB1/B2-independent way\u003c/h2\u003e\u003cp\u003eOur previous work identified GABPA as a key regulator in the establishment of na\u0026iuml;ve pluripotency. However, the mechanisms by which GABPA governs gene expression remain poorly understood. To define its direct function, we generated GABPA-dTAG mESCs(Zhou et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Consistent with phenotypes reported in \u003cem\u003eGabpa\u003c/em\u003e conditional knockout mice(Ueda et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), GABPA depletion led to rapid cell death, with cells failing to survive beyond 24 hours (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, A and B, fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eA). Notably, time-course analysis revealed that hallmarks of apoptosis and cell cycle dysregulation emerged as early as 9 hours post-GABPA depletion (fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e, B and C), preceding overt cell death. Taken together, these findings establish GABPA as a core survival factor in mESCs and highlight the utility of acute depletion strategies in dissecting its immediate regulatory functions, bypassing the confounding secondary effects associated with chronic loss-of-function models.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eGABPA is canonically known to function as a DNA-binding subunit that forms a heterotetrameric complex with GABPB1 or GABPB2, both of which have the trans-activator domain. During mouse early embryonic development, the expression of \u003cem\u003eGabpa\u003c/em\u003e and \u003cem\u003eGabpb1\u003c/em\u003e reach to peak from late 2 cell stage, whereas \u003cem\u003eGabpb2\u003c/em\u003e remains expressed at consistently low levels throughout this window (fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eD), suggesting that GABPB1 is the predominant cofactor for GABPA in early embryos and potentially in mESCs. To directly test whether GABPA requires GABPB1 to maintain mESC viability, we generated a GABPB1-dTAG mESC line enabling acute degradation of GABPB1 protein (fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eE). Surprisingly, GABPB1 depletion had minimal impact on mESC survival and proliferation, as cells remained viable and morphologically indistinguishable from controls over extended culture (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, A and B). This unexpected observation prompted us to examine potential compensation by GABPB2. Although \u003cem\u003eGabpb2\u003c/em\u003e expression is low, we simultaneously targeted both GABPB1 and GABPB2 using the dTAG system (fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eF). Dual depletion impaired cell proliferation, but the phenotype was substantially milder and occurred later than that observed following GABPA loss (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, A and B). These findings suggest that while GABPB1 and GABPB2 may contribute partially to GABPA function, GABPA may possess GABPB-independent functions critical for mESC viability.\u003c/p\u003e\u003cp\u003eFurthermore, transcriptome analysis after 12 hours of protein degradation (fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eG, table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e) revealed that GABPA depletion resulted in widespread transcriptional dysregulation, with approximately 1,500 differentially expressed genes (DEGs), including both up- and downregulated genes (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC), GABPB1 depletion alone had a negligible effect on gene expression, resulting in only 57 DEGs (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD). Combined depletion of GABPB1 and GABPB2 increased the number of DEGs to 246, yet the overall transcriptional impact remained modest compared to the extensive changes triggered by GABPA loss (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eE). Moreover, a substantial proportion of genes downregulated upon GABPB1 or GABPB1/B2 depletion were also downregulated following GABPA loss (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eF, fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eH), suggesting that the transcriptional activity of GABPB1/B2 depends on the presence of GABPA. However, the vast majority of GABPA-regulated genes were unaffected by the loss of either or both cofactors, indicating that GABPA controls a large gene regulatory network independently of its conventional heterotetrameric partners during this time window. Collectively, these findings demonstrate that GABPA is the primary driver of the transcriptional program required for mESC survival in an unanticipated, GABPB1/B2-independent mode of action.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eGABPA interacts with core transcriptional machinery in mESCs\u003c/h3\u003e\n\u003cp\u003eTo uncover potential cofactors that collaborate with GABPA to support mESC survival, we performed immunoprecipitation followed by mass spectrometry (IP-MS) in GABPA-dTAG mESCs using an HA antibody to selectively enrich endogenous GABPA complexes (fig. \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e, A and B). Comparison between the DMSO-treated control and the dTAG-induced GABPA-depleted group revealed 175 proteins significantly enriched in the presence of GABPA (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003eA, table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e), representing candidate GABPA interactors. As expected, the most highly enriched proteins were GABPB1 and GABPB2, in line with the canonical model in which GABPA forms a DNA-binding heterotetramer with GABPB subunits to drive transcription (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). Interestingly, several previously reported GABPA interactors, such as Sp1 and CBP/P300 in myeloid cells(Bush et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2003\u003c/span\u003e), and Mettl23 in neuroblasts(Reiff et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), were not detected in the mESC GABPA interactome, suggesting that GABPA engages in highly cell type-specific protein-protein interactions.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eFunctional annotation of the 175 enriched proteins revealed that GABPA predominantly associates with factors involved in transcription regulation, chromatin organization, and RNA processing (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003e, A and B). Notably, components of the transcription elongation and pause-release machinery were among the top interactors, including INTS4, SPT5, and LARP7 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). INTS4 serves as the scaffold subunit of the catalytically active endonuclease module of the Integrator complex (containing INTS4/9/11)(Elrod et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Zheng et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). SPT5 is a multifunctional regulator and its rapid depletion caused a reduction of paused Pol II at promoter-proximal region (Aoi et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Hu et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). LARP7 is a 3\u0026rsquo;RNA stability protein and it stably associated with the 7SK snRNP to regulate P-TEFb activity(Krueger et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Of particular interest, INTS4/9/11 complex were recently shown to be essential for mESC survival(Hu et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), mirroring the phenotype observed upon GABPA loss.\u003c/p\u003e\u003cp\u003eTo validate these interactions, we performed endogenous co-immunoprecipitation (Co-IP) using HA antibodies in GABPA-dTAG mESCs. Consistent with the mass spectrometry results, HA-tagged GABPA robustly co-immunoprecipitated with INTS4, as well as INTS11, the catalytic subunit of the Integrator endonuclease module (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003e, C and D). In addition, GABPA also interacted with RNA polymerase II (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003eC), suggesting a potential role in transcriptional regulation through recruitment or modulation of the transcriptional machinery. Several additional interactors involved in RNA metabolism and chromatin regulation, including ANLN, DDX21, NPM1, and SPT5, were also validated via Co-IP (fig. \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003eC), corroborating the specificity of the GABPA interactome.\u003c/p\u003e\u003cp\u003eTo investigate whether these physical interactions are functionally relevant, we examined the chromatin occupancy of GABPA and its interactors. Chromatin profiling revealed that a large proportion (56%) of GABPA-bound genomic loci were co-occupied by INTS11, particularly at promoter-proximal region (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003eE). Motif enrichment analysis of INTS11 peaks further revealed a strong overrepresentation of ETS motifs (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003eF), suggesting that GABPA may serve as a DNA-targeting factor for the Integrator complex. Together, these findings identify the INTS4/9/11 module as a previously unrecognized effector of GABPA function in mESCs and uncover a potential mechanistic link between TF-mediated chromatin binding and Integrator-driven transcriptional control.\u003c/p\u003e\n\u003ch3\u003eGABPA recruits INTS4/9/11 complex to regulate the expression of ribosome biogenesis related genes\u003c/h3\u003e\n\u003cp\u003eAlthough the Integrator complex plays key roles in transcriptional regulation, its recruitment mechanisms remain unclear due to the absence of intrinsic DNA-binding domains. Recent structural evidence indicates that TFs can serve as chromatin-recruiting platforms for Integrator via direct protein-protein interactions(Razew et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Given the physical interaction between GABPA and the INTS4/9/11 endonuclease module, we hypothesized that GABPA may function as a DNA-anchored recruiter of Integrator to support gene expression programs essential for mESC viability.\u003c/p\u003e\u003cp\u003eTo further investigate how GABPA cooperates with the INTS4/9/11 module to regulate gene expression, we performed SLAM-seq to monitor global nascent transcription following GABPA depletion (fig. \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003eA). Cells were treated with dTAG for 12 hours, a time point chosen to capture early transcriptional changes prior to widespread cell death. This analysis identified 2,820 differentially expressed genes (DEGs), of which a striking 94.5% were downregulated (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). Among these downregulated genes, approximately 18% belonged to the early post-implantation (EPI) gene set (fig. \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003eB), consistent with our previous findings implicating GABPA function in the establishment of na\u0026iuml;ve pluripotency(Zhou et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Gene ontology (GO) enrichment analysis revealed that GABPA-activated genes are significantly associated with biological processes involved in ribonucleoprotein complex biogenesis and RNA processing (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e3\u003c/span\u003eB), suggesting a role for GABPA in coordinating biosynthetic and growth-related pathways critical for mESC viability.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eTo determine whether these effects were mediated by direct GABPA binding, we integrated SLAM-seq data with GABPA CUT\u0026amp;RUN profiles. Remarkably, 47% of the GABPA-responsive DEGs were directly bound by GABPA (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e3\u003c/span\u003e, C and D). There was a strong positive correlation between the extent of nascent RNA downregulation and the number of canonical GABPA binding motifs within promoter regions (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e3\u003c/span\u003eE, fig. \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003eC), supporting a model of direct transcriptional regulation. To further elucidate the mechanistic link between GABPA and the Integrator complex, we compared the transcriptional profiles of mESCs following acute depletion of GABPA (this study) and INTS11(Wang et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Although only around 25% of DEGs overlapped in these two groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e3\u003c/span\u003eF), GO analysis of the overlapping DEGs revealed a pronounced enrichment for genes involved in ribonucleoprotein complex biogenesis (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e3\u003c/span\u003eG), consistent with the notion that GABPA may recruit the Integrator complex to control this essential biosynthetic program.\u003c/p\u003e\u003cp\u003eTo directly test whether GABPA facilitates the chromatin recruitment of the INTS4/9/11 complex, we performed CUT\u0026amp;Tag profiling of INTS11 in control and GABPA-depleted mESCs. Strikingly, GABPA depletion led to a marked global reduction of INTS11 occupancy at shared target genes (fig. \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003eA, Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e3\u003c/span\u003e, H and I), indicating that GABPA is required for stable association of the INTS4/9/11 complex with chromatin. Taken together, these data support a model in which GABPA functions as a chromatin-anchored recruiter of the INTS4/9/11 module to activate transcription of genes essential for RNA processing and ribonucleoprotein complex assembly.\u003c/p\u003e\n\u003ch3\u003eAcute depletion of GABPA leads to blockage of RNA Pol II elongation\u003c/h3\u003e\n\u003cp\u003eGiven that GABPA protein is efficiently depleted within 1 hour of dTAG treatment (fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eA), we next sought to distinguish primary transcriptional responses from secondary downstream effects. To this end, we conducted time-resolved SLAM-seq at 1, 2, and 4 hours post-GABPA depletion to monitor nascent RNA dynamics and identify genes directly responsive to acute GABPA loss (fig. \u003cspan refid=\"MOESM4\" class=\"InternalRef\"\u003eS4\u003c/span\u003eA, table \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003e). Strikingly, as early as 1 hour post-depletion, we detected significant downregulation of 100 genes (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e4\u003c/span\u003eA), indicating that GABPA controls a set of genes with rapid and direct transcriptional sensitivity to its absence. The number of downregulated genes increased in a time-dependent manner, with 281 and 498 genes significantly downregulated at 2 and 4 hours, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e4\u003c/span\u003e, B to E, fig. \u003cspan refid=\"MOESM4\" class=\"InternalRef\"\u003eS4\u003c/span\u003eB), consistent with an expanding transcriptional cascade triggered by GABPA loss. Notably, GO analysis revealed a consistent and strong enrichment for genes involved in ribonucleoprotein complex biogenesis across all early time points (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e4\u003c/span\u003eF, fig. \u003cspan refid=\"MOESM4\" class=\"InternalRef\"\u003eS4\u003c/span\u003e, C and D). And the GABPA CUT\u0026amp;RUN signals are enriched around the TSS of significantly down-regulated genes at 1, 2, and 4 hours (fig. \u003cspan refid=\"MOESM4\" class=\"InternalRef\"\u003eS4\u003c/span\u003eE). These findings closely mirror the transcriptional landscape observed at the 12-hour time point (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e3\u003c/span\u003eC), suggesting that GABPA rapidly activates a core transcriptional program critical for RNA processing, ribosome assembly, and cellular fitness in mESCs.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eTo determine whether these early transcriptional effects were accompanied by changes in chromatin state, we assessed chromatin accessibility and active histone modifications after acute GABPA depletion. ATAC-seq and CUT\u0026amp;Tag profiling of H3K27ac and H3K4me3 were performed at 1 hour post-treatment (fig. S5A). In contrast to the transcriptional repression observed, no significant changes were observed in global chromatin accessibility or histone modification levels at this early time point (fig. S5, B to D). These results suggest that GABPA does not regulate gene expression by remodeling chromatin structure or enhancer/promoter activation during the immediate early response.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eGiven the physical and functional interaction between GABPA and the INTS4/9/11 complex, we next asked whether GABPA acute depletion affect the Integrator endonuclease module recruitment to promoter-proximal region. To address this, we profiled INTS11 occupancy at 1 hour post-GABPA depletion using CUT\u0026amp;Tag. Notably, INTS11 binding at promoter-proximal regions of the 100 rapidly downregulated genes was significantly reduced following GABPA acute depletion (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e5\u003c/span\u003e, A to D). Given that Integrator endonuclease module has been previously implicated in facilitating transcriptional elongation(Hu et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), we then hypothesized that GABPA may regulate gene expression in mESCs by promoting transcription elongation. To test this, we examined the distribution of RNA polymerase II (Pol II) phosphorylation marks using CUT\u0026amp;Tag, focusing on Serine 5-phosphorylated (pSer5) and Serine 2-phosphorylated (pSer2) forms, which are enriched at transcription start sites (TSSs) and gene bodies, respectively, and serve as proxies for initiation and elongation states. Upon acute GABPA depletion, we observed no substantial change in either pSer5 or pSer2 occupancy at promoter regions of GABPA target genes (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e5\u003c/span\u003e, E to G), suggesting that Pol II recruitment and initiation remain largely intact. In contrast, pSer2 signal within gene bodies was markedly reduced (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e5\u003c/span\u003e, E to G), indicating a defect in productive transcriptional elongation. This selective loss of gene body associated Pol II pSer2 signal, in the absence of chromatin accessibility or histone mark alterations, suggests that GABPA cooperates with INTS4/9/11 complex to regulate transcription through a mechanism that facilitates Pol II elongation.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\n\u003ch3\u003eProlonged GABPA depletion impairs chromatin accessibility and general transcription machinery\u003c/h3\u003e\n\u003cp\u003eWhile acute GABPA loss primarily disrupts transcription elongation without affecting chromatin accessibility, we next asked whether prolonged depletion impacts chromatin state. To address this, we performed ATAC-seq and CUT\u0026amp;Tag for H3K27ac and H3K4me3 following 12 hours of GABPA depletion (fig. S6, A to C). Cells were harvested 12 hours after dTAG treatment to capture early chromatin changes prior to extensive cell death. Genome-wide ATAC-seq analysis revealed a modest yet significant reduction in chromatin accessibility at promoter region of GABPA-affected genes (Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e6\u003c/span\u003e, A to C), indicating that GABPA contributes to the maintenance of an open chromatin state. CUT\u0026amp;Tag profiling further demonstrated concordant decreases in both H3K27ac and H3K4me3 signal intensities at these loci (Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e6\u003c/span\u003e, A to C), hallmark modifications of transcriptionally active chromatin. These data suggest that GABPA may facilitate the epigenetic landscape conducive to gene expression.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eTo determine whether GABPA affects core components of the transcriptional machinery, we examined RNA Pol II phosphorylation status. Western blot analysis revealed a pronounced reduction in both Ser5 and Ser2 phosphorylation after GABPA depletion for 12 hours (Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e6\u003c/span\u003eD), indicative of impaired transcriptional initiation and elongation, respectively. Consistently, the protein levels of CDK7 and CDK9, cyclin-dependent kinases essential for Pol II CTD phosphorylation during promoter clearance and productive elongation, were also markedly decreased (Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e6\u003c/span\u003eD). Consistently, CUT\u0026amp;Tag for pSer5 and pSer2 also showed significant decrease of pSer5 and pSer2 signal intensities at promoter and gene body, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e6\u003c/span\u003eB). These observations raise the possibility that GABPA may interface with broader regulatory networks beyond Integrator. Indeed, our IP-MS analysis identified multiple putative GABPA interactors involved in transcriptional regulation and epigenetic modification (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003eB), suggesting that its role in sustaining the transcriptional machinery may extend beyond its immediate impact on pause release. Collectively, these results demonstrate that GABPA maintains mESC transcription through temporally distinct mechanisms: an immediate role in promoting Pol II pause-release and transcription elongation via Integrator complex recruitment, followed by a later role in sustaining chromatin accessibility, active histone modifications, and the phosphorylation state of Pol II and its associated kinases. Together, these functions establish GABPA as a central regulator of transcriptional competence in mESCs.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe dynamic regulation of gene expression by TFs is central to cellular identity and function. Yet, defining the immediate molecular consequences of TF loss has remained challenging due to compensatory adaptations that arise with conventional gene deletion or knockdown strategies. These long-term perturbations often blur the distinction between direct and indirect effects by allowing time for secondary transcriptional and epigenetic remodeling. In this study, we leveraged an acute degradation system to dissect the primary transcriptional roles of the ETS family transcription factor GABPA in mESCs, revealing an unanticipated function in the regulation of transcriptional elongation through interaction with the Integrator complex.\u003c/p\u003e\u003cp\u003eBy degrading GABPA within 1 hour, we captured early and direct transcriptional responses to its loss while minimizing secondary adaptations. Time-resolved SLAM-seq analysis revealed that GABPA is required for the rapid transcriptional activation of a core gene module, predominantly composed of ribonucleoprotein biogenesis and RNA processing genes. These transcriptional effects preceded any detectable changes in chromatin accessibility or active histone modifications, arguing strongly against GABPA acting through canonical chromatin remodeling or enhancer priming mechanisms during this early response phase. Instead, our data point to a distinct mechanism by which GABPA modulates transcriptional output. We identified a physical and functional interaction between GABPA and the INTS4/9/11 endonuclease module of the Integrator complex, a multifunctional regulator known to promote Pol II elongation. Consistently, acute GABPA depletion led to a global reduction in INTS11 occupancy at shared target genes, implicating GABPA as a key recruiter of the Integrator endonuclease complex to chromatin. Functionally, this recruitment appears to be critical for proper transcriptional elongation. Our integrative analysis revealed that acute GABPA depletion selectively impaired RNA Pol II elongation dynamics. While Pol II initiation remained largely unaffected, gene body-associated pSer2 levels were markedly reduced at GABPA target genes. This supports a model in which GABPA recruits Integrator to facilitate the transition from paused to elongating Pol II, thereby ensuring productive transcription of genes critical for mESC viability (Fig.\u0026nbsp;\u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eNotably, this elongation-centered role of GABPA diverges from classical paradigms in which TFs primarily modulate chromatin accessibility or initiation complex assembly. Our findings thus expand the conceptual framework for transcriptional regulation by TFs, illustrating how a sequence-specific DNA-binding factor can exert gene-selective effects through elongation-phase control. In this context, the rapid downregulation of ribosome biogenesis genes following GABPA depletion suggests that these loci are particularly reliant on uninterrupted elongation, positioning them as early sensors of transcriptional stress in stem cells.\u003c/p\u003e\u003cp\u003eBeyond this primary mechanism, our GABPA interactome analysis revealed additional cofactor, including SPT5, LARP7, NPM1, ANLN, and DDX21, that may contribute to broader transcriptional and RNA processing networks. Intriguingly, prolonged depletion of GABPA resulted in widespread transcriptional dysregulation, potentially mediated by these alternative interactors, raising the possibility that GABPA serves as a multifaceted scaffold coordinating multiple layers of gene expression control. This is further supported by the phenotypic disparity observed between GABPA and GABPB1/B2 depleted mESCs. While GABPA is canonically known to function as a heterotetramer with GABPB1 or GABPB2, our data and prior studies suggest that GABPA harbors additional functions independent of its known partners, possibly via interaction with other chromatin associated proteins.\u003c/p\u003e\u003cp\u003eIn summary, our findings identify GABPA as a critical regulator of transcriptional elongation in mESCs and establish a direct mechanistic link between DNA-bound transcription factors and the elongation machinery. This work not only redefines the functional repertoire of GABPA but also highlights the power of acute perturbation strategies in resolving primary transcriptional regulatory mechanisms. More broadly, our work suggests that TF-driven modulation of Pol II elongation dynamics represents an underappreciated axis of gene regulation, particularly relevant for sustaining the biosynthetic demands of rapidly proliferating cells such as pluripotent stem cells.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003eCell culture\u003c/h2\u003e\u003cp\u003eThe ES-B6 cells (from National Stem Cell Resource Center) were cultured on 0.1% gelatin-coated plates with 2i/LIF (MEKi/GSK3i/leukemia inhibitory factor) condition. Cells were grown in DMEM-high glucose (Gibco 11960044), supplemented with 15% fetal bovine serum (FBS)(Gibco 10099141, VISTECH SE200-ES), 100 U/mL penicillin\u0026ndash;streptomycin (Gibco, 15140122), 2 mM L-Glutamine (Life technologies A2916801), 1 mM sodium pyruvate (MP Biomedicals, 219965480), 0.084 mM 2-mercaptoethanol (Gibco, 21985023), 1\u0026times; MEM NEAA (Life technologies, 11140050), 1,000 IU/mL LIF (Sigma-Aldrich, ESG1107), 0.5 \u0026micro;M PD0325901 (Millipore, 444966-5mg), and 3 \u0026micro;M CHIR99021 (Selleck, S1263).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eGenome editing for dTAG endogenous knock-in\u003c/h2\u003e\u003cp\u003eTo establish \u003cem\u003eGabpa\u003c/em\u003e\u003csup\u003e\u003cem\u003edTAG/dTAG\u003c/em\u003e\u003c/sup\u003e and \u003cem\u003eGabpb1\u003c/em\u003e\u003csup\u003e\u003cem\u003edTAG/dTAG\u003c/em\u003e\u003c/sup\u003e cells by the endogenous knock-in, \u003cem\u003eGabpa-\u003c/em\u003eHAL-FKBP\u003csup\u003eF36V\u003c/sup\u003e-2xHA-HAR, \u003cem\u003eGabpb1-\u003c/em\u003eHAL-FKBP\u003csup\u003eF36V\u003c/sup\u003e-2xHA-HAR and px330 plasmids were transfected into mESCs with Lipofectamine\u0026trade; 2000 (Invitrogen, 11668030). Primers for plasmid construction are listed in table \u003cspan refid=\"MOESM4\" class=\"InternalRef\"\u003eS4\u003c/span\u003e. 24 hours after transfection, cells were selected with 1 \u0026micro;g/mL puromycin (Invitrogen, A1113803) for another 48 hours. Then cells were cultured in puromycin-free medium for one week. Single-clone colonies were picked, expanded, and genotyped by genomic DNA PCR targeting the integration site. For homogeneous knock-in clones, protein degradation efficiency was verified by 500nM dTAG-13 treatment for 1 hour followed by Western Blotting. \u003cem\u003eGabpb1\u003c/em\u003e\u003csup\u003e\u003cem\u003edTAG/dTAG\u003c/em\u003e\u003c/sup\u003e cells were used as the parental line to generate \u003cem\u003eGabpb1/b2\u003c/em\u003e\u003csup\u003e\u003cem\u003edTAG/dTAG\u003c/em\u003e\u003c/sup\u003e cells following the similar process described above.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eWestern blot\u003c/h2\u003e\u003cp\u003eA total of 1\u0026times; 10\u003csup\u003e6\u003c/sup\u003e cells were lysed in 100 \u0026micro;L RIPA lysis buffer and incubated on ice for 30 mins. The lysate was centrifuged at 120,00 rpm for 30 mins at 4\u0026deg;C and the supernatant was collected. Protein extracts were quantified by BCA protein assay kit (Thermo Scientific, 23227), following manufacturer\u0026rsquo;s instructions. 90 \u0026micro;L of supernatant was mixed with 12.5 \u0026micro;L 5\u0026times; loading buffer, and heated at 98\u0026deg;C for 15 mins. Samples were run on Precast Protein Plus Gel, 4\u0026ndash;12%, Bis-Tris (Yeasen, 36269ES10) and transferred onto polyvinylidene fluoride transfer (PVDF) membrane. Primary antibodies used included anti-GABPA (1:4,000, Proteintech, 21542-1-AP), anti-HA (1:1,000, Cell Signaling Technology, 3724S and 2367S), anti-Flag (1:1,000, Proteintech, 66008-4-Ig), anti-GAPDH (1:5,000, Abmart, M20006M), anti-β-actin (1:5,000, Cell Signaling Technology, 4967S), Pol II (1:1000, Cell Signaling Technology, 14958S), pSer2 (1:900, Abcam, Ab5095), pSer5 (1:1000, Cell Signaling Technology, 13523S), CDK7 (1:1000, Abcam, ab256787), anti-CDK9 (1:1000, Cell Signaling Technologies, 2316), ANLN (1:500, Santa Cruz, sc-271814), anti-DDX21 (1:5000, ProteinTech, 10528-1-AP), NPM1 (1:1000, Abmart, PK66455S), INT4 (1:1000, ProteinTech, 16130-1-AP), INT11 (1:300, ProteinTech, 15860-1-AP; 1:5000, Bethyl Labs, A301-274A). Secondary antibodies used included goat anti-Rabbit IgG (H\u0026thinsp;+\u0026thinsp;L) secondary antibody-HRP (1:5000, Beijing Ray Antibody Biotech, RM3001) and goat anti-mouse IgG (H\u0026thinsp;+\u0026thinsp;L) secondary antibody-HRP (1:5000, Beijing Ray Antibody Biotech, RM3002). Protein bands were detected with an enhanced chemiluminescence (ECL) kit and imaged by Tanon 4600SF Imaging System.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eCell proliferation assay\u003c/h2\u003e\u003cp\u003e1.5\u0026times;10\u003csup\u003e5\u003c/sup\u003e cells were seeded in a 6-well plate. After culturing for 24 hours, cells were treated with DMSO or 500 nM dTAG-13 (Sigma-Aldrich, SML2601), and counted every 24 hours for 3 consecutive days by Invitrogen Countess 3.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eAnalysis of apoptosis\u003c/h2\u003e\u003cp\u003eCell apoptosis analysis using Annexin V-PE Apoptosis Detection Kit (Keygen Biotech, KGA1030) in accordance to manufacturer\u0026rsquo;s instructions. Briefly, cells were washed with PBS and dissociated by treatment with trypsin-EDTA. Single cell suspension was washed twice with PBS/2% BSA, and 1\u0026thinsp;~\u0026thinsp;5\u0026times;10\u003csup\u003e5\u003c/sup\u003e cells were resuspended in 500 \u0026micro;L of Binding Buffer. 5 \u0026micro;L of FITC-Annexin V and PI were added and cells were incubated at room temperature for 5\u0026thinsp;~\u0026thinsp;10 mins in dark. Cells were left on ice and subjected to flow cytometry analysis within 1 hour on the BD FACSAria Fusion cell sorter. Data were acquired and analyzed using FlowJo version 10.8.1 software.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003eCell cycle analysis\u003c/h2\u003e\u003cp\u003eCell cycle was detected with propidium iodide and a cell cycle detection kit (Keygen Biotech, KGA512) according to the manufacturer\u0026rsquo;s protocols. Briefly, cells were washed with PBS and dissociated by treatment with trypsin-EDTA. 1.5\u0026times;10\u003csup\u003e6\u003c/sup\u003e cells were fixed overnight at 4\u0026deg;C with 70% cold ethanol. Before staining, cells were with PBS, and then incubated with 500 \u0026micro;L of the pre-prepared PI/RNase A staining working solution in the dark at room temperature for 30\u0026thinsp;~\u0026thinsp;60 mins. Cells were detected on the BD FACSAria Fusion cell sorter, and the red fluorescence was recorded at an excitation wavelength of 488 nm. Data were acquired and analyzed using FlowJo version 10.8.1 software.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003eImmunoprecipitation and Mass spectrometry\u003c/h2\u003e\u003cp\u003emESCs were lysed in lysis buffer (20 mM HEPES pH 7.4, 140 mM NaCl, 2 mM MgCl\u003csub\u003e2\u003c/sub\u003e, 10% glycerol, 0.5% NP-40, 0.2 mM EDTA, 2 mM dithiothreitol (DTT), and 1\u0026times; protease inhibitor) for 30 mins on ice. The lysate was centrifuged at 20,000 g for 30 mins at 4\u0026deg;C and the supernatant was collected and incubated with anti-HA Magnetic beads (MedChemExpress, HY-K0201) for 2 hours at 4\u0026deg;C. For Co-Immunoprecipitation (Co-IP), 2 \u0026micro;g INTS4 (ProteinTech, 16130-1-AP) or INTS11 (Bethyl Labs, A301-274A) antibodies overnight at 4\u0026deg;C. Pierce\u0026trade; Protein A/G Magnetic Beads (Thermo, 88802) were washed three times with beads wash buffer (50 mM Tris-HCl, 150 mM NaCl, 0.5% Tween-20 pH 7.4). Pre-washed magnetic beads were added to the cells with gentle vortexing. Samples were incubated at room temperature with mixing for 1 hour. Beads were collected with a magnetic stand and washed three times with lysis buffer and twice with wash buffer. After washing five times as above, SDS loading buffer (100 mM Tris pH 7.5, 4%SDS, 10 mM DTT) was directly mixed with the beads. Supernatant was mixed with 5\u0026times; loading buffer, and heated at 95\u0026deg;C for 10 mins for western blotting detection.\u003c/p\u003e\u003cp\u003eFor mass spectrometry, proteins were immunoprecipitated with anti-HA Magnetic beads. After washing five times, SDS loading buffer (100 mM Tris pH 7.5, 4% SDS, 10 mM DTT) was directly mixed with the beads for western blotting detection and proteins were cut from gels for mass spectrometry. the gel containing proteins was cut into pieces and de-stain in 25 mM ammonium bicarbonate/50% acetonitrile buffer. After decolored, the proteins were reduced with 10 mM DTT in 50 mM ammonium bicarbonate at 56 ℃ for 1 hour and alkylated with 55 mM iodoacetamide in 50 mM ammonium bicarbonate in the dark for 45 mins, and digested with trypsin at 37 ℃ overnight. Peptides were extracted from gel with buffers containing 5% trifluoroacetic acid and 50% acetonitirile by ultrasonic twice. The liquid was freeze dried by SpeedVac, and peptides were desalted by StageTip.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003eLC-MS/MS analysis and Protein Identification\u003c/h2\u003e\u003cp\u003ePeptides were resuspended in 0.1% FA and analyzed by LTQ Orbitrap Elite mass spectrometer (ThermoFisher Scientific) coupled online to an Easy-nLC 1000 (Thermo Fisher Scientific) in the data-dependent mode. The peptides were separated by reverse phase LC with an 150 \u0026micro;m (ID) \u0026times;250 mm (length) analytical column packed with C18 particles of 1.9 \u0026micro;m diameter. The mobile phases for the LC contains buffer A (0.1% FA ) and buffer B (100% ACN, 0.1% FA), and a non-linear gradient of buffer B from 3%-30% for 90 min was used for the separation. Precursor ions were measured in the Orbitrap analyzer at 240,000 resolution (at 400 m/z) and a target value of 10^\u003csup\u003e6\u003c/sup\u003e ions. The tweenty most intense ions from each MS scan were isolated, fragmented, and measured in the linear ion trap. The CID normalized collision energy was set to 35.\u003c/p\u003e\u003cp\u003eThe database search was performed for all raw MS files using the software MaxQuant (version 2.3.1.0). The Mus musculus proteome sequence database (21701 entries) from UniProt was applied to searching the data. The parameters used for the database search were set up as follows: Type: standard; Multiplicity: 1; The protease used for protein digestion: trypsin; Label free quantification: LFQ; The minimum score for unmodified peptides: 15. Default values were used for all other parameters.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003eATAC-seq\u003c/h2\u003e\u003cp\u003eATAC\u0026ndash;seq was performed as previously described with modification(Zhang et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Briefly, mESCs cells were digested with adapter-loaded Tn5 (Vazyme, S604-01) in the tagmentation buffer (33 mM Tris-Acetate, 66 mM K-Acetate, 10 mM Mg-Acetate,16% DMF, 0.02% Digitonin) for 30 mins at 37\u0026deg;C, and the reaction was stopped by stop buffer (100 mM Tris pH 8.0, 100 mM NaCl, 0.4% SDS and 40 \u0026micro;g/mL Proteinase K) and incubated overnight at 55\u0026deg;C. 25% Tween-20 was added to quench SDS. Sequencing libraries were prepared with NEBNext High-Fidelity 2\u0026times; PCR Master Mix. The PCR product was purified using a 1:1.6 volume ratio of SPRI beads. After 10 mins incubation at RT the beads were washed twice with 180\u0026thinsp;~\u0026thinsp;200 \u0026micro;L 80% freshly-prepared ethanol on the magnetic stand and the dried beads pellets were resuspended in 20\u0026micro;L RNAse free water. Libraries were quantified by Equalbit 1\u0026times; dsDNA HS Assay Kit (Vazyme, EQ121-02) and quality was checked using Fragment Analyzer 12 with DNF-474-0500 HS NGS Fragment Kit (Agilent, 9994).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\u003ch2\u003eSLAM-seq\u003c/h2\u003e\u003cp\u003eSLAM-seq was performed as previously described with modifications. mESCs were cultured with culture medium containing 500 \u0026micro;M 4-thiouridine (4sU) for 1 or 2 hours to metabolically label newly synthesized RNA. Cells were detached using Trypsin/EDTA and washed twice in cold PBS after centrifugation at 600\u0026times;g and finally resuspended in cold PBS. 6\u0026times;10\u003csup\u003e4\u003c/sup\u003e cells were lysed in 10\u0026micro;L lysis buffer (10 mM Tris-HCl pH 7.5, 10 mM NaCl, 3 mM MgCl, 2 U/\u0026micro;l RNase inhibitor, 0.02% Digitonin), and incubated at room temperature for at least 3mins, then put on ice. After frozen on dry ice, the lysate was thawed at room temperature for 3-5mins. Total RNA was thiol-linked alkylated by iodoacetamide (IAA) for 15 mins at 50\u0026deg;C in a mixture containing 10 mM IAA, 1x PBS, and 50% DMSO. Alkylation was stopped by adding DTT to 15 mM. The 4sU-labeled RNA was isolated using a 1:1 volume of RNA XP magnetic beads. After 10 mins incubation at room temperature, the beads were washed twice with 180\u0026thinsp;~\u0026thinsp;200 \u0026micro;L 80% freshly-prepared ethanol on the magnetic stand and the dried beads pellets were resuspended in 7 \u0026micro;L RNAse free water. 1 \u0026micro;L of 10 \u0026micro;M Oligo-dT primer and 1 \u0026micro;L of 10 mM dNTP were added into the 4sU-labeled RNA. After incubation at 72\u0026deg;C for 3 mins, and samples were placed on ice for 2 mins. 9.5 \u0026micro;L of the Reverse Transcription Mix containing 0.5 \u0026micro;L of 40 U/\u0026micro;L RNase Inhibitor and 1 \u0026micro;L of 200 U/\u0026micro;L SuperScript II Reverse Transcriptase were added for reverse transcription. The reaction was performed according to the manual using the following PCR conditions: 42\u0026deg;C for 90 mins; thermocycling for 10 cycles at 50\u0026deg;C for 2 mins, 42\u0026deg;C for 2 mins; followed by 70\u0026deg;C for 15 mins; and holding at 4\u0026deg;C. Amplification was performed by adding 25 \u0026micro;L of 2\u0026times; KAPA HiFi Master Mix, 4.5 \u0026micro;L of Nuclease-free water and 0.5 \u0026micro;L of 10 \u0026micro;M ISPCR primer mix into the first-strand reaction sample. After PCR amplification, cDNAs were isolated using a 1:1.1 volume of SPRI beads. Libraries were quantified by Equalbit 1\u0026times; dsDNA HS Assay Kit (Vazyme, EQ121-02) and quality was checked using Fragment Analyzer12 with DNF-474-0500 HS NGS Fragment Kit (Agilent, 9994) .\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\u003ch2\u003eCleavage under targets and tagmentation (CUT\u0026amp;Tag) assay\u003c/h2\u003e\u003cp\u003eThe CUT\u0026amp;Tag assay was performed as previously described with modifications(Kaya-Okur et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), using the Hyperactive Universal CUT\u0026amp;Tag Assay Kit for Illumina (Vazyme Biotech, TD903). Briefly, mESCs cells were washed with 500 \u0026micro;L wash buffer and centrifuged at 600\u0026times; g for 5 mins at room temperature. 1\u0026times; 10\u003csup\u003e5\u003c/sup\u003e cells were captured with concanavalin A-coated magnetic beads. The bead-bound cells were resuspended with 50 \u0026micro;L antibody buffer containing rabbit anti-pSer2 (1:50, Abcam, Ab5095), pSer5 (1:50, Cell Signaling Technology, 13523S), H3K4me3 (1:50, Active Motif, 39016), H3K27ac (1:50, Active Motif, 39034). After incubation overnight at 4\u0026deg;C, the primary antibody was carefully discarded and 0.5 \u0026micro;L Goat Anti-Rabbit IgG H\u0026amp;L (1:100, Vazyme, Ab207-01) diluted with 50 \u0026micro;L Dig-wash buffer was added to the cells. The cells were then incubated with rotation at room temperature for 1 hour. After washing gently with 200 \u0026micro;L Dig-wash buffer, 2 \u0026micro;L pA/G\u0026ndash;Tnp together with 98 \u0026micro;l Dig-300 buffer was added to the samples. After incubating at room temperature for 1 hour, the samples were washed gently with 200 \u0026micro;L Dig-300 buffer. Then, 10 \u0026micro;L 5\u0026times; TTBL mixed with 40 \u0026micro;L Dig-300 buffer was added to each sample and incubated at 37\u0026deg;C for 1 hour. The reactions were stopped by adding 5 \u0026micro;L 20 mg/ml Proteinase K, 100 \u0026micro;L Buffer L/B, and 20 \u0026micro;L DNA extraction beads and incubating at 55\u0026deg;C for 10 mins. The supernatant was discarded and the beads were washed once with 200 \u0026micro;L Buffer WA and twice with 200 \u0026micro;L Buffer WB and resuspended with 21 \u0026micro;L nuclease free water. For library amplification, 20 \u0026micro;L of purified DNA was mixed with 25 \u0026micro;L of 2\u0026times; CAM, along with 2.5 \u0026micro;L of uniquely barcoded i5 and i7 primers. A total volume of 50 \u0026micro;L of sample was placed in a PCR thermal cycler using the following program: 72\u0026deg;C for 3 mins; 98\u0026deg;C for 3 mins; thermocycling for 11 cycles at 98\u0026deg;C for 10 secs, 60\u0026deg;C for 5 secs, followed by 72\u0026deg;C for 1 mins; and holding at 4\u0026deg;C. PCR products were purified with SPRI beads. All libraries were sequenced by Novogene using the Illumina NovaSeq 6000 platform in PE150 mode (Novogene, Beijing, China).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e\u003ch2\u003eStatistics\u003c/h2\u003e\u003cp\u003eSignificant differences between groups (DMSO vs dTAG) were tested using GraphPad Prism (GraphPad Software Version 10.4.1). The number of samples used per experiment is presented in figures or figure legends. Tests used to calculate statistical significance are mentioned in figure legends. All data are presented as means\u0026thinsp;\u0026plusmn;\u0026thinsp;SDs. A \u003cem\u003eP\u003c/em\u003e value of 0.05 was considered statistically significant. In the histogram and curve, \u003cem\u003eP\u003c/em\u003e*\u0026lt;0.05, \u003cem\u003eP\u003c/em\u003e**\u0026lt;0.01, \u003cem\u003eP\u003c/em\u003e***\u0026lt;0.001, \u003cem\u003eP\u003c/em\u003e****\u0026lt;0.0001, and ns (not significant) are indicated.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec22\" class=\"Section2\"\u003e\u003ch2\u003eCoIP-MS data analysis\u003c/h2\u003e\u003cp\u003eRaw acquisition files of the proteome samples were analyzed together with MaxQuant (v2.3)(Cox and Mann, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Then, the proteinGroups.txt result tables were analyzed and visualized with R package DEP2 (v0.5.28.2)(Zhang et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2018a\u003c/span\u003e). Data was filtered by missing value, normalized using vsn and imputed. Proteins were considered differentially enriched when the fold change was greater than 2, and the \u003cem\u003eP\u003c/em\u003e value was lower than 0.05. The volcano plot was generated in ggplot2 (v3.5.1).\u003c/p\u003e\u003cdiv id=\"Sec23\" class=\"Section3\"\u003e\u003ch2\u003eRNA-seq data analysis\u003c/h2\u003e\u003cp\u003eThe raw paired-end RNA-seq reads were trimmed with Trim Galore (v0.6.7) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.bioinformatics.babraham.ac.uk/projects/trim_galore\u003c/span\u003e\u003cspan address=\"https://www.bioinformatics.babraham.ac.uk/projects/trim_galore\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Then, the cleaned reads were mapped to the GRCm39 genome by STAR (v2.7.11a)(Dobin et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) and the gene annotation file was downloaded from GENECODE (vM32)(Frankish et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). RSEM (v1.3.1)(Li and Dewey, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) was used to calculate gene expression levels and DESeq2 (v1.44.0)(Love et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) was applied to identify differentially expressed genes. The significantly differentially expressed genes were called with an adjusted \u003cem\u003eP\u003c/em\u003e value cut-off of 0.05 and a fold change cut-off of 2. Gene ontology (GO) analysis was performed using R package clusterProfiler (v4.12.6)(Yu et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) and enrichplot (v1.24.2) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://github.com/YuLab-SMU/enrichplot\u003c/span\u003e\u003cspan address=\"https://github.com/YuLab-SMU/enrichplot\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec24\" class=\"Section2\"\u003e\u003ch2\u003eSLAM-seq data analysis\u003c/h2\u003e\u003cp\u003eAdapters were trimmed from raw reads using Cutadapt (v3.5) through the Trim Galore (v0.6.7) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.bioinformatics.babraham.ac.uk/projects/trim_galore\u003c/span\u003e\u003cspan address=\"https://www.bioinformatics.babraham.ac.uk/projects/trim_galore\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) wrapper tool. SLAM-seq analyses were performed using the SLAMdunk pipeline (v0.4.3)(Neumann et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), which includes mapping, read filtering, single-nucleotide polymorphism (SNP) variant calling, conversion counts and rate calculation. MultiQC and separate BAM files for labeled and unlabeled reads using the Alleyoop collapse program from SlamDunk. The significantly differentially expressed genes were called using DESeq2 (v1.44.0)(Love et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) with size factors estimated on corresponding total mRNA reads for global normalization with an adjusted \u003cem\u003eP\u003c/em\u003e value cut-off of 0.05 and fold change cut-off of 2. GO analysis was performed similarly to RNA-seq.\u003c/p\u003e\u003cdiv id=\"Sec25\" class=\"Section3\"\u003e\u003ch2\u003eATAC-seq and CUT\u0026amp;Tag data analysis\u003c/h2\u003e\u003cp\u003eThe paired-end raw reads were first trimmed of the adaptors with Trim Galore (v0.6.7) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.bioinformatics.babraham.ac.uk/projects/trim_galore\u003c/span\u003e\u003cspan address=\"https://www.bioinformatics.babraham.ac.uk/projects/trim_galore\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and then aligned to the GRCm39 genomes using Bowtie2 (v2.4.4)(Langmead and Salzberg, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) with the following parameters: --no-unal --no-mixed --no-discordant. Low mapping quality reads (MAPQ\u0026thinsp;\u0026lt;\u0026thinsp;30), unmapped reads and duplicated reads were removed using Sambamba (v1.0.1)(Tarasov et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), Picard (v2.21.4) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://broadinstitute.github.io/picard/\u003c/span\u003e\u003cspan address=\"https://broadinstitute.github.io/picard/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and SAMtools (v1.13)(Li et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). For the histone modification CUT\u0026amp;Tag, the mapped reads were further filtered to retain only proper paired reads with fragment length at least 178bp. Read coverages over the genome were estimated by bamCoverage from deepTools (v3.5.1)(Ramirez et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) with the following parameters: --binSize 20 --minMappingQuality 30 --scaleFactor 1 --normalizeUsing RPKM, and visualized by Integrative Genomics Viewer (IGV) (v2.16.2)(Thorvaldsdottir et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec26\" class=\"Section3\"\u003e\u003ch2\u003eMotif enrichment analysis\u003c/h2\u003e\u003cp\u003eThe motif files were acquired from the JASPAR database(Rauluseviciute et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) and converted to HOMER motif format by dumpJaspar with R package monaLisa (v1.11.1)(Machlab et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The locations of GABPA motifs in the genome-wide were determined using scanMotifGenomeWide.pl from HOMER (v5.0.1)(Heinz et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2010\u003c/span\u003e), and the quantity of motifs present in the promoters was assessed by overlapping them with genome-wide motif locations. The JASPAR motif IDs for GABPA is MA0062.2.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec27\" class=\"Section3\"\u003e\u003ch2\u003eData availability\u003c/h2\u003e\u003cp\u003eAll data generated in this study have been deposited to the NCBI Gene Expression Omnibus (GEO) with accession number GSE304514 (Token for reviewers\u0026rsquo; access: qlufeasmznqpbgf). Mouse oocyte to eight-cell and E3.5 ICM RNA-seq data from GSE71434(Zhang et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) and GSE76505(Zhang et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2018b\u003c/span\u003e), respectively. GABPA CUT\u0026amp;RUN data from GSE263171(Zhou et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). INTS11 ChIP-seq and SLAM-seq from GSE181714(Wang et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data generated in this study have been deposited to the NCBI Gene Expression Omnibus (GEO) with accession number GSE304514 (Token for reviewers’ access: qlufeasmznqpbgf). Mouse\u0026nbsp;oocyte to eight-cell and E3.5 ICM RNA-seq data from GSE71434(Zhang et al., 2016) and GSE76505(Zhang et al., 2018b), respectively. GABPA CUT\u0026amp;RUN data from GSE263171(Zhou et al., 2025). INTS11 ChIP-seq and SLAM-seq from GSE181714(Wang et al., 2023).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank Dr. Jingsi Tang for her valuable discussions on the project and comments on the manuscript. This project was supported by the National Natural Science Foundation of China (32370865). We thank Professor Yingchun Wang and Dr. Xiahe Huang (the Institute of Genetics and Developmental Biology of the Chinese Academy of Sciences) for providing technical support for mass spectrometry. We thank Ting Li (the Institute of Genetics and Developmental Biology of the Chinese Academy of Sciences) for her excellent technical assistance in flow cytometry.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eC-X.Z. conceived and supervised the project. H.Y. performed all the bioinformatic analysis. J-J.G. established GABPB1-dTAG and GABPB1/B2-dTAG ESCs, and performed the experiments including RNA-seq, SLAM-seq, CoIP-MS, ATAC-seq etc. B-Q.W. performed the CUT\u0026amp;Tag. H.Y., J-J.G and C-X.Z. wrote the manuscript. All authors interpreted the data and reviewed the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAbuhashem A, Lee AS, Joyner AL, Hadjantonakis AK (2022) Rapid and efficient degradation of endogenous proteins in vivo identifies stage-specific roles of RNA Pol II pausing in mammalian development. Dev Cell 57:1068\u0026ndash;1080e1066\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAoi Y, Takahashi YH, Shah AP, Iwanaszko M, Rendleman EJ, Khan NH, Cho BK, Goo YA, Ganesan S, Kelleher NL et al (2021) SPT5 stabilization of promoter-proximal RNA polymerase II. Mol Cell 81:4413\u0026ndash;4424e4415\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBush TS, St Coeur M, Resendes KK, Rosmarin AG (2003) GA-binding protein (GABP) and Sp1 are required, along with retinoid receptors, to mediate retinoic acid responsiveness of CD18 (beta 2 leukocyte integrin): a novel mechanism of transcriptional regulation in myeloid cells. Blood 101:311\u0026ndash;317\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCox J, Mann M (2008) MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification. Nat Biotechnol 26:1367\u0026ndash;1372\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDobin A, Davis CA, Schlesinger F, Drenkow J, Zaleski C, Jha S, Batut P, Chaisson M, Gingeras TR (2013) STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29:15\u0026ndash;21\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eElrod ND, Henriques T, Huang KL, Tatomer DC, Wilusz JE, Wagner EJ, Adelman K (2019) The Integrator Complex Attenuates Promoter-Proximal Transcription at Protein-Coding Genes. Mol Cell 76:738\u0026ndash;752e737\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFrankish A, Carbonell-Sala S, Diekhans M, Jungreis I, Loveland JE, Mudge JM, Sisu C, Wright JC, Arnan C, Barnes I et al (2023) GENCODE: reference annotation for the human and mouse genomes in 2023. Nucleic Acids Res 51:D942\u0026ndash;D949\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHeinz S, Benner C, Spann N, Bertolino E, Lin YC, Laslo P, Cheng JX, Murre C, Singh H, Glass CK (2010) Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities. Mol Cell 38:576\u0026ndash;589\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHu S, Peng L, Song A, Ji YX, Cheng J, Wang M, Chen FX (2023) INTAC endonuclease and phosphatase modules differentially regulate transcription by RNA polymerase II. Mol Cell 83:1588\u0026ndash;1604e1585\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHu S, Peng L, Xu C, Wang Z, Song A, Chen FX (2021) SPT5 stabilizes RNA polymerase II, orchestrates transcription cycles, and maintains the enhancer landscape. Mol Cell 81:4425\u0026ndash;4439e4426\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eIsbel L, Grand RS, Schubeler D (2022) Generating specificity in genome regulation through transcription factor sensitivity to chromatin. Nat Rev Genet 23:728\u0026ndash;740\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKaya-Okur HS, Wu SJ, Codomo CA, Pledger ES, Bryson TD, Henikoff JG, Ahmad K, Henikoff S (2019) CUT\u0026amp;Tag for efficient epigenomic profiling of small samples and single cells. Nat Commun \u003cem\u003e10\u003c/em\u003e, 1930\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKrueger BJ, Jeronimo C, Roy BB, Bouchard A, Barrandon C, Byers SA, Searcey CE, Cooper JJ, Bensaude O, Cohen EA et al (2008) LARP7 is a stable component of the 7SK snRNP while P-TEFb, HEXIM1 and hnRNP A1 are reversibly associated. Nucleic Acids Res 36:2219\u0026ndash;2229\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLambert SA, Jolma A, Campitelli LF, Das PK, Yin Y, Albu M, Chen X, Taipale J, Hughes TR, Weirauch MT (2018) Hum Transcription Factors Cell 172:650\u0026ndash;665\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLangmead B, Salzberg SL (2012) Fast gapped-read alignment with Bowtie 2. Nat Methods 9:357\u0026ndash;359\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLi B, Dewey CN (2011) RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinformatics 12:323\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLi H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, Marth G, Abecasis G, Durbin R (2009) The Sequence Alignment/Map format and SAMtools, vol 25. Bioinformatics, pp 2078\u0026ndash;2079. and Genome Project Data Processing\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLove MI, Huber W, Anders S (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15:550\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMachlab D, Burger L, Soneson C, Rijli FM, Schubeler D, Stadler MB (2022) monaLisa: an R/Bioconductor package for identifying regulatory motifs. Bioinformatics 38:2624\u0026ndash;2625\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNabet B, Roberts JM, Buckley DL, Paulk J, Dastjerdi S, Yang A, Leggett AL, Erb MA, Lawlor MA, Souza A et al (2018) The dTAG system for immediate and target-specific protein degradation. Nat Chem Biol 14:431\u0026ndash;441\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNeumann T, Herzog VA, Muhar M, von Haeseler A, Zuber J, Ameres SL, Rescheneder P (2019) Quantification of experimentally induced nucleotide conversions in high-throughput sequencing datasets. BMC Bioinformatics 20:258\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNishimura K, Fukagawa T, Takisawa H, Kakimoto T, Kanemaki M (2009) An auxin-based degron system for the rapid depletion of proteins in nonplant cells. Nat Methods 6:917\u0026ndash;922\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRamirez F, Ryan DP, Gruning B, Bhardwaj V, Kilpert F, Richter AS, Heyne S, Dundar F, Manke T (2016) deepTools2: a next generation web server for deep-sequencing data analysis. Nucleic Acids Res 44:W160\u0026ndash;165\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRauluseviciute I, Riudavets-Puig R, Blanc-Mathieu R, Castro-Mondragon JA, Ferenc K, Kumar V, Lemma RB, Lucas J, Cheneby J, Baranasic D et al (2024) JASPAR 2024: 20th anniversary of the open-access database of transcription factor binding profiles. Nucleic Acids Res 52:D174\u0026ndash;D182\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRazew M, Fraudeau A, Pfleiderer MM, Linares R, Galej WP (2024) Structural basis of the Integrator complex assembly and association with transcription factors. Mol Cell 84:2542\u0026ndash;2552e2545\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eReiff RE, Ali BR, Baron B, Yu TW, Ben-Salem S, Coulter ME, Schubert CR, Hill RS, Akawi NA, Al-Younes B et al (2014) METTL23, a transcriptional partner of GABPA, is essential for human cognition. Hum Mol Genet 23:3456\u0026ndash;3466\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eResendes KK, Rosmarin AG (2006) GA-binding protein and p300 are essential components of a retinoic acid-induced enhanceosome in myeloid cells. Mol Cell Biol 26:3060\u0026ndash;3070\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSawada J, Simizu N, Suzuki F, Sawa C, Goto M, Hasegawa M, Imai T, Watanabe H, Handa H (1999) Synergistic transcriptional activation by hGABP and select members of the activation transcription factor/cAMP response element-binding protein family. J Biol Chem 274:35475\u0026ndash;35482\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSharrocks AD (2001) The ETS-domain transcription factor family. Nat Rev Mol Cell Biol 2:827\u0026ndash;837\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSoto LF, Li Z, Santoso CS, Berenson A, Ho I, Shen VX, Yuan S, Bass F, J.I (2022) Compendium of human transcription factor effector domains. Mol Cell 82:514\u0026ndash;526\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSpitz F, Furlong EE (2012) Transcription factors: from enhancer binding to developmental control. Nat Rev Genet 13:613\u0026ndash;626\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eStadhouders R, Filion GJ, Graf T (2019) Transcription factors and 3D genome conformation in cell-fate decisions. Nature 569:345\u0026ndash;354\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTakahashi K, Tanabe K, Ohnuki M, Narita M, Ichisaka T, Tomoda K, Yamanaka S (2007) Induction of pluripotent stem cells from adult human fibroblasts by defined factors. Cell 131:861\u0026ndash;872\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTarasov A, Vilella AJ, Cuppen E, Nijman IJ, Prins P (2015) Sambamba: fast processing of NGS alignment formats. Bioinf 31, 2032\u0026ndash;2034\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eThompson CC, Brown TA, McKnight SL (1991) Convergence of Ets- and notch-related structural motifs in a heteromeric DNA binding complex. Science 253:762\u0026ndash;768\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eThorvaldsdottir H, Robinson JT, Mesirov JP (2013) Integrative Genomics Viewer (IGV): high-performance genomics data visualization and exploration. Brief Bioinform 14:178\u0026ndash;192\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eUeda A, Akagi T, Yokota T (2017) GA-Binding Protein Alpha Is Involved in the Survival of Mouse Embryonic Stem Cells. Stem Cells 35:2229\u0026ndash;2238\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWang H, Fan Z, Shliaha PV, Miele M, Hendrickson RC, Jiang X, Helin K (2023) H3K4me3 regulates RNA polymerase II promoter-proximal pause-release. Nature 615:339\u0026ndash;348\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYu G, Wang LG, Han Y, He QY (2012) clusterProfiler: an R package for comparing biological themes among gene clusters. Omics 16:284\u0026ndash;287\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhang B, Zheng H, Huang B, Li W, Xiang Y, Peng X, Ming J, Wu X, Zhang Y, Xu Q et al (2016) Allelic reprogramming of the histone modification H3K4me3 in early mammalian development. Nature 537:553\u0026ndash;557\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhang C, Chen Z, Yin Q, Fu X, Li Y, Stopka T, Skoultchi AI, Zhang Y (2020) The chromatin remodeler Snf2h is essential for oocyte meiotic cell cycle progression. Genes Dev 34:166\u0026ndash;178\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhang X, Smits AH, van Tilburg GB, Ovaa H, Huber W, Vermeulen M (2018a) Proteome-wide identification of ubiquitin interactions using UbIA-MS. Nat Protoc 13:530\u0026ndash;550\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhang Y, Xiang Y, Yin Q, Du Z, Peng X, Wang Q, Fidalgo M, Xia W, Li Y, Zhao ZA et al (2018b) Dynamic epigenomic landscapes during early lineage specification in mouse embryos. Nat Genet 50:96\u0026ndash;105\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZheng H, Qi Y, Hu S, Cao X, Xu C, Yin Z, Chen X, Li Y, Liu W, Li J et al (2020) Identification of Integrator-PP2A complex (INTAC), an RNA polymerase II phosphatase. Sci 370\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhou C, Wang M, Zhang C, Zhang Y (2025) The transcription factor GABPA is a master regulator of naive pluripotency. Nat Cell Biol 27:48\u0026ndash;58\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"GABPA, INTAC, transcription elongation","lastPublishedDoi":"10.21203/rs.3.rs-7297262/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7297262/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eTranscription factors (TFs) coordinate gene regulatory programs essential for cell identity and fate, yet the mechanisms by which individual TFs modulate distinct stages of transcription remain incompletely understood. GABPA, an ETS family transcription factor, was recently identified as a critical regulator of na\u0026iuml;ve pluripotency in mouse embryonic stem cells (mESCs), but its molecular functions have remained elusive. Here, we employ an acute protein degradation system to dissect GABPA activity with high temporal resolution, enabling the identification of immediate transcriptional targets and mechanisms while avoiding secondary effects associated with conventional gene knockouts. We find that GABPA is essential for mESC viability through a previously unrecognized mechanism that is independent of its canonical heterotetrameric partner, GABPB. Mechanistically, GABPA physically engages the INTS4/9/11 endonuclease module of the Integrator complex to facilitate RNA polymerase II (Pol II) pause-release at ribosome biogenesis genes, promoting productive transcription elongation. Acute GABPA depletion leads to a marked reduction of gene body-associated Ser2-phosphorylated Pol II, indicative of defective elongation. In contrast, prolonged GABPA loss results in diminished chromatin accessibility and enhancer activity at pluripotency-associated loci. Together, these findings reveal dual temporally distinct roles for GABPA, an immediate function in transcriptional elongation and a later function in chromatin regulation. Our study redefines GABPA as a multifaceted transcriptional regulator acting independently of GABPB, and provides a framework for temporally resolved dissection of TF function in stem cell biology.\u003c/p\u003e","manuscriptTitle":"GABPA Recruits the Integrator Endonuclease Complex to Promote Transcription Elongation","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-19 08:36:16","doi":"10.21203/rs.3.rs-7297262/v1","editorialEvents":[],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"nature-communications","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"NCOMMS","sideBox":"Learn more about [Nature Communications](http://www.nature.com/ncomms/)","snPcode":"","submissionUrl":"https://mts-ncomms.nature.com/","title":"Nature Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature Communications","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"f48a8d3c-3f7d-4bb6-a66d-1b710f229959","owner":[],"postedDate":"September 19th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":54960026,"name":"Biological sciences/Genetics/Gene regulation"},{"id":54960027,"name":"Biological sciences/Developmental biology/Stem cells/Embryonic stem cells"}],"tags":[],"updatedAt":"2025-11-10T18:16:06+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-19 08:36:16","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7297262","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7297262","identity":"rs-7297262","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}