AKAP95 condensates regulate transcription and can be targeted in MLL-fusion driven oncogenesis

Domain: chemistry
Published: 2026-01-07
Editorial outcome: accept

Abstract
RNA binding proteins could regulate transcription through modulating RNA polymerase II involved transcriptional condensates with the aid of nascent RNA. However, whether this mechanism also contributes to tumorigenesis is still unknown. Here, we show the RBP AKAP95 is required for MLL rearranged leukemogenesis. Phase separation and RNA binding properties of AKAP95 modulate Pol II recruitment into condensates at genome-wide target sites. AKAP95 interact with MLL1 translocated fragment and their partial co-condensation leads to stronger AKAP95 binding towards MLL-AF9 target genes. Loss of AKAP95 significantly downregulates expression of MLL-AF9 targets and impairs MLL-AF9 driven leukemogenesis. AKAP95 is not essential for normal and regenerative hematopoiesis, rendering it an ideal target for leukemia therapeutics. As an endeavor for modifying condensates, we design a peptide JD-PI95 bridging AKAP95 to protein quality surveillance component HSP70. The peptide successfully impairs AKAP95 phase separation, attenuates gene transcription and inhibits MLLr leukemia cells proliferation. Our work demonstrates an important role of RBP condensates in tumorigenesis through regulation of transcription and a new method to perturb specific condensates for tumor inhibition.

Introduction
Phase-separation involved transcriptional machinery assembly provides exciting insights to explain many puzzles in eukaryotic transcription regulation. Transcriptional condensates, initiated through the multivalent interaction among the intrinsic disordered regions (IDRs) of transcription factors, coactivators, mediators, chromatin remodelers and RNA polymerase II (Pol II), control several steps of gene activation, including preinitiation complex formation, transcription pausing and elongation, super-enhancer assembly, and mRNA splicing and processing1. Meanwhile, chromatin and newly synthesized RNAs modulate transcriptional condensate formation. Chromatin acts as a scaffold recruiting multivalent transcription-related molecules to trigger the formation of transcriptional condensates2. The yield of nascent RNAs determines the formation or dissolution of transcriptional condensates, working as feedback for transcription activation3.

RNA-binding proteins (RBPs) could bind to nascent RNAs, making them particularly important in studying how transcriptional condensates are modulated by other factors. Many pieces of evidence hint that RBPs and transcription factors, or Pol II, are engaged in the same condensates to regulate transcription. For example, RMB25 had much overlapped genomic binding with YY1, and facilitated the latter’s role in transcription activation4. WDR43 binding to 7SK RNA was intertwined with Pol II pause release, suggesting multiple biomolecular interactions occurring at mesoscale5. PSPC1 is a paradigm of how RBPs and RNA synergistically facilitate Pol II condensation and promote transcription in mouse embryonic stem cells6. However, whether RBPs modulation of transcriptional condensate formation is an underlying mechanism for tumorigenesis is still unknown.

Aberrant protein phase separation could be the potential cause for many cancers. Oncogenic proteins, ENL mutants, EWS-FLI1, and NUP98-HOXA9, acquired phase separation for persistent transcription activation to allow tumor cells rapid proliferation7–9. EML4-ALK fusion protein forming condensate in cytoplasm activated JAK-STAT pathway, leading to the transition of lung adenosquamous cell carcinoma from adenomatous to squamous pathologies10,11. On the other hand, emerging understanding about the molecular basis for these oncogenic condensates provides new opportunities to treat cancer. High-throughput screening of drugs identified LY2835219, which effectively dissolved EWS-FLI1 condensates and rescued EWS-FLI1-induced aberrant gene expression12. A peptide (FIP4) targeting FOXM1-IDR1 disrupted FOXM1 liquid-liquid phase separation, reduced breast tumor growth and metastasis13. Although condensate-modifying therapeutics is at its infancy, it is a promising avenue for treating condensate-driven diseases14.

We previously reported that an RBP, AKAP95, regulates pre-mRNA splicing15,16. Besides scaffolding RBPs, AKAP95 also interacted with many transcription/chromatin-associated proteins (Pol II, MLL2, DPY30, HDAC3)16–18. AKAP95 protein has a phase-separation property, which mediates its splicing activity and pro-oncogenic function. It is still unclear if and how AKAP95 regulates tumorigenesis through transcription, and how its phase separation property might be targeted for tumor control.

In this study, we found that AKAP95 was overexpressed in MLL rearranged (MLLr) leukemia compared to other types of leukemia. It is well known that oncogenic transcription underlies MLLr leukemogenesis19. We found a two-layer mechanism of transcription regulation by AKAP95 in cells. Phase separation and RNA binding properties of AKAP95 modulate Pol II recruitment into the transcriptional condensates at genome-wide target sites. AKAP95 interaction with MLL1 translocated fragment and their partial co-condensation enhanced AKAP95 binding with MLL-AF9 target genes, resulting in higher dependence of the MLLr leukemia-specific transcriptome on AKAP95. We also took advantage of host cell heat shock proteins in safeguarding protein homeostasis, designed a molecular tool to target AKAP95 phase separation, and tested its therapeutic function in inhibiting MLLr leukemia cell proliferation.

Results
AKAP95 is essential for MLLr leukemogenesis
Through analyzing the MLL-fusion proteins interactome20, we found AKAP95 is one hit with 4 different MLL-fusion proteins (MLL-AF9, MLL-EEN, MLL-ENL, MLL-GAS7). This enticed us to check whether it plays an important role in MLLr leukemia. Firstly, we referred to the transcriptome of MLLr and non-MLL rearranged (non-MLLr) leukemias in different cohorts21–23. The mRNA level of AKPA95 was significantly upregulated in both MLLr acute myeloid leukemia (AML) and B-cell acute lymphoblastic leukemia (B-ALL) compared to the non-MLLr leukemias (Fig. 1a, b). AKAP95 expression was also higher in MLLr leukemia cells than the normal hemopoiesis stem cells (HSC) (Fig. 1c). We confirmed this result by quantitative PCR analysis of 16 primary AML patient bone marrow samples (MLLr, n = 5; non-MLLr, n = 11), and western blot analysis of several leukemia cell lines (Fig. 1d and Supplementary Fig. 1a, b). Moreover, both the previous mouse MLL-AF9 leukemia model24 and our own experiment showed that Akap95 was upregulated in Lin− bone marrow cells transduced by MLL-AF9 lentiviral vector compared to the counterpart (Fig. 1e). These data suggest that AKAP95 may play an important role in MLLr leukemia.

To address this question, we knocked down AKAP95 in different leukemia cell lines by shRNA lentiviral vectors. The result showed that only MLLr leukemia cell lines THP-1 (MLL-AF9), Molm13 (MLL-AF9) and MV411 (MLL-AFF1) were impaired in cell growth, but not the non-MLLr K562 (BCR-ABL) and HL-60 (TP53−/−) cells (Fig. 1f and Supplementary Fig. 1c). CRISPR score was below zero and negatively correlated with AKAP95 expression in AML cell lines in the DepMap dataset (Supplementary Fig. 1d). These data indicate that AKAP95 is critical for MLLr leukemia cells.

Using our previously established Akap95−/− mouse15, we investigated whether Akap95 is important for MLL-AF9-driven leukemogenesis. We transformed Lin− bone marrow from wildtype (WT) and Akap95−/− mice with MLL-AF9-IRES-GFP or MLL-AF9-IRES-RFP retroviral vector. Both types of cells had the similar transduction rate (Supplementary Fig. 2a). Then, we injected them into conditioned recipient mice through the tail vein. The recipients with WT cells transplantation succumbed to leukemia significantly faster than the recipients with Akap95−/− cells transplantation (WT median survival: 51 days; KO median survival: 93 days; P=0.0007) (Fig. 2a). When bone marrow harvest from the moribund recipients were subjected to Wright-Giemsa staining, WT bone marrow showed a more undifferentiated phenotype than Akap95−/− bone marrow (Fig. 2b). Immunostaining also showed that more myeloid progenitor cells (GFP+Lin−ckit+Mac1+Gr1+)25 existed in WT bone marrow (Fig. 2c). As a surrogate for assessing myeloid transformation, colony formation activity of transformed Akap95−/− cells was greatly reduced in the serial replating assay. Akap95−/− cells formed less compact and smaller colonies with the appearance of differentiated neutrophils/macrophages (Fig. 2d, e). We repeated the colony formation assay with sorted RFP positive cells and obtained a similar result (Supplementary Fig. 2b). For the colonies grown out in the third plating, we transferred them into liquid culture and harvested the cells for a western blot to check MLL-AF9 expression. WT and Akap95−/− transformed cells had a similar amount of MLL-AF9 expressed (Supplementary Fig. 2c). These results indicate that Akap95 is critical for efficient leukemogenesis driven by MLL-AF9.

From the primary leukemic bone marrow, we harvested the LGMP population (Lin−GFP+cKit+CD34+CD16/32+)24 (Supplementary Fig. 2d) and transplanted them into secondary recipients. The disease latency was greatly shortened, but WT leukemia cells still had stronger potency to cause recipients death (WT median survival: 25.5 days; KO median survival: 28 days; P=0.0022) (Fig. 2f), and to form colonies in serial replating (Fig. 2g).

We have previously shown that Akap95 is dispensable for homeostatic hematopoiesis15, but it remains unknown if it is important for hematopoietic reconstitution. We carried out competitive transplantation assays by transplanting CD45.2-marked WT or Akap95−/− bone marrow cells with CD45.1 bone marrow cells at a 1:1 ratio (Supplementary Fig. 3a). Mice receiving the Akap95−/− cells showed similar bone marrow, spleen, and periphery blood chimerism in all lineages as WT cells (Supplementary Fig. 3b–d). Together, all these data suggest that AKAP95 is required for efficient MLLr leukemogenesis, but not for normal hematopoiesis under either homeostatic or regenerative conditions.

Loss of Akap95 impairs MLL-AF9-induced transcriptome
We performed RNA-seq for the MLL-AF9 lentiviral vector transduced WT and Akap95−/− bone marrow cells 48 h post-infection. Totally, 674 genes' mRNA levels showed significant changes between WT and KO cells, with 377 genes upregulated and 295 genes downregulated (|log fold change|>0.58) (Fig. 2h, Supplementary Data 1). Gene ontology analysis showed that the molecular functions of downregulated genes were mainly associated with transcription regulation, while upregulated ones were specified in cell adhesion (Supplementary Fig. 4a). Moreover, the targets of HOXA9, MEIS1, and MYC were preferentially enriched in genes downregulated in the KO cells (Supplementary Fig. 4b). We confirmed the downregulation of several well-established MLL-AF9 targets and upregulation of myeloid cell differentiation marker genes (Itgam, Cd14) in Akap95−/− pre-leukemia cells by quantitative PCR (Fig. 2i). Metagene analysis showed that active transcription markers (H3K27Ac and H3K4Me3) were enriched more in WT than in Akap95−/− bone marrow cells (Supplementary Fig. 5a). To be specific, several well-established MLL-AF9 target (Meis1, Pbx3, and Cpeb2) loci had more H3K27ac modification in WT cells, while Itgam and Cd14 loci had a little more H3K4me3 modification in KO cells (Supplementary Fig. 5b), supporting the phenotypic difference.

AKAP95 interacts with MLL1 translocated fragment mainly through the IDR
To investigate the endogenous AKAP95 condensates in cells, we established the endogenous Flag-mEGFP-AKAP95 knock-in Hela (Hela KI) cells by CRISPR/Cas9 technique (Supplementary Fig. 6a–c). Both of the two positive cell clones showed discrete foci of endogenous AKAP95 in the nucleus. FRAP assay showed a fast recovery of the fluorescent signals (T1/2 = 4.12 ± 1.31 s) in the AKAP95 condensate after bleaching (Fig. 3a). To confirm the interaction of AKAP95 and MLL-fusion protein, we carried out two different assays, Co-IP and imaging method. Endogenous AKAP95 were immunoprecipitated together with overexpressed flag-HA-MLL1T (MLL1 translocated fragment) in 293T cells (Fig. 3b). When mcherry-MLL1T were expressed in Hela KI cells, AKAP95 condensates had partial co-localization signals with mcherry-MLL1T (Fig. 3c). To dissect the binding moiety of AKAP95, we made a series of constructs expressing individual regions of AKAP95 (aa1–100, aa101–390, aa391–550, aa551–692) according to the prediction of disordered region (Fig. 3d). Co-transfection of GFP-fused individual fragments with mcherry-MLL1T showed that aa101–390 (IDR1), but not the other fragments, co-localized with MLL1T and formed large aggregates in the nucleus. Replacing the previously reported six Tyrosine residues in aa101–210 with Serine (PS-mutant) abolished the co-condensation (Fig. 3e). We speculated that AKAP95 IDR1 interacts with largely disordered MLL1T (Supplementary Fig. 6d), somewhat similar to how transcription activation domain (also disordered) interacts with IDRs of many co-activator26. AKAP95 IDR1 had similar rates of negative and positive charged residues as MLL1T, while its net charge per residues was negative, matching the positive net charge per residues of MLL1T (Supplementary Fig. 6e, f). The assembly of AKAP95 and MLL1T into co-condensates may be the molecular basis for AKAP95’s critical involvement in MLLr leukemogenesis.

AKAP95 binds to the genome prevalently and contributes to gene transcription
To investigate AKAP95 function in transcription regulation, we carried out anti-flag ChIP-seq to analyze the genome-wide binding sites of the endogenous AKAP95. The result showed that there were 5656 binding sites of AKAP95 in the genome. Most of the binding sites were located in promoters (59.23%), followed by introns (17.27%) and intergenic regions (12.14%) (Fig. 4a and Supplementary Data 2). The vicinity of AKAP95-binding regions was enriched with DNA-binding motifs of transcription factors NFY, Sp1 and YY1, which are critical for stem cell fate determination and proliferation27–29 (Supplementary Fig. 7a). Since enhancers are usually located in intergenic regions or introns, we checked whether AKAP95 binding sites fall within the reported enhancers in Hela cells30. 408 typical enhancers and 36 super enhancers showed significant enrichment in AKAP95-bound sites (Supplementary Fig. 7b). These data suggest that AKAP95 may have important roles in regulating gene expression.

Compared with control, knockdown of AKAP95 in Hela cells altered expression of 4270 genes (2372 genes down-regulated, 1898 genes up-regulated, Supplementary Fig. 7c, d and Supplementary Data 3). The down-regulated genes were enriched in AKAP95-binding promoters/genes (n=414, P<0.0001, Fig. 4b). Interestingly, a core subset of MLL-AF9 targets19 (n=177) were also enriched in AKAP95 binding promoters/genes (n=56, P<0.0001), and had significantly higher AKAP95 binding intensity than the rest promoters/genes, suggesting AKAP95 may contribute to MLL-AF9 activated transcription (Fig. 4c, d). Indeed, the down-regulation degree of the AKAP95 and MLL-AF9 joint targets (n=18) was significantly greater than that of other AKAP95 targets (Fig. 4d, e, g and Supplementary Data 4).

We also checked AKAP95-bound RNAs in Hela cells by CLIP-seq. Totally, we identified 2078 RNA-binding sites, corresponding to 1837 mRNA targets. The top RNA-binding sites were categorized into intron (61.26%), followed by promoter (13.47%) and exon (9.33%) (Supplementary Fig. 7e). A quarter of AKAP95 CLIP-targets also had ChIP-binding at the DNA level (Supplementary Fig. 7f).

RNA-binding and phase separation are required for AKAP95 binding to the genome and regulating transcription
We next sought to dissect how AKAP95 as an RBP might regulate transcription. AKAP95 binds to RNA through its zinc finger (ZF) domains16, and has the property of phase separation (PS)15. To check if these two features play roles in AKAP95 binding to chromatin, we established the Hela Flp-In-Trex cells stably expressing AKAP95 (WT or ZF-mutant or PS-mutant)-GFP fusion protein (Supplementary Fig. 8a). Through the cell fractionation process (Fig. 5a), we compared ZF-, PS-mutant subcellular localization to that of AKAP95-WT. ZF- and PS-mutants were easier to be released into the cytoplasmic fraction (S1) after hypotonic treatment than both exogenous and endogenous AKAP95-WT protein (Fig. 5b), likely due to their reduced chromatin-association in the nucleus. For the nuclear fraction (P1), exogenous and endogenous AKAP95 stayed more in the insoluble fraction (chromatin, P2) than in the soluble fraction (nucleoplasm, S2) in the absence of RNase treatment, but this localization status dramatically inverted after RNase treatment. PS-mutant behaved similarly to AKAP95-WT. But ZF-mutant was not responsive to RNase treatment. Moreover, a short treatment with Actinomycin (for 4h), inhibiting transcription, impaired AKAP95 binding to genomic targets as shown in the ChIP-seq analysis (Supplementary Fig. 8b). These data indicate that RNA-binding property is required for AKAP95 binding to chromatin. To measure the intensity of chromatin-associated AKAP95, we treated the P2 fraction with micrococcal nuclease (MNase) and checked the released (S3) and the leftover (P3) portions. Both exogenous and endogenous AKAP95 WT proteins were gradually released into supernatant fraction in a time-dependent manner, but ZF- and PS-mutants had much higher rates in S3 before the MNase treatment and exhibited minimal release further into S3 following the MNase treatment (Fig. 5c and Supplementary Fig. 8c). These results indicate both RNA binding and phase separation properties are required for efficient binding of AKAP95 to chromatin.

Using a chromosomally integrated luciferase reporter gene HEK293T cell line (G-293T)17, we checked AKAP95 variants function in coactivating gene transcription. The results showed that both ZF- and PS-mutant were impaired in activating luciferase gene expression, most likely at the transcriptional level since the reporter gene has no intron (Supplementary Fig. 8d). Then, we checked the genome-wide transcription in the presence of AKAP95-WT, ZF- and PS-mutant individually. To avoid the endogenous AKAP95 interference, we first depleted endogenous AKAP95 by shRNA in the aforementioned established Hela stable cell lines (Supplementary Fig. 8e). We carried out ChIP-seq analysis for total Pol II (RPB1) and actively elongating Pol II, which is phosphorylated at serine 2 of its C-terminal domain (Ser2P). The result showed more occupancy of total Pol II at the promoters in the ZF- and PS-mutant cells than in the AKAP95-WT cells (Fig. 5d). But the mutant cells showed lower Pol II (Ser2P) binding signals across gene bodies than WT cells (Supplementary Fig. 8f). Precision nuclear run-on and sequencing (Pro-seq) analysis also showed that the on-going transcription rates of AKAP95 targets were reduced in mutant cells than in WT cells (Fig. 5e and Supplementary Fig. 9). The degree of Ser2P signals reduction in AKAP95 target genes was positively correlated with the densities of AKAP95 ChIP-seq reads and the level of mRNA down-regulation in both ZF- and PS-mutant compared to the WT control (Supplementary Fig. 8g, h), suggesting that the stronger a target gene is bound by AKAP95, the more reliant it is on both the RNA binding and phase separation properties of AKAP95 for the active transcription of this target gene. These combined data indicate that RNA-binding and phase separation are required for the activity of AKAP95 in driving active transcription.

Previously, we reported that AKAP95 co-immunoprecipitated with Pol II (RPB1) in cells and partially colocalized with Pol II Ser2P15,16. By immunofluorescence staining, we found that ZF-mutant formed discrete foci but hardly overlapped with Pol II Ser2P, and PS-mutant was largely diffusive in the nucleus (Fig. 5f). We purified recombinant AKAP95 and Pol II CTD (aa1356-1767, including 23 heptapeptide repeats) and confirmed AKAP95 directly bound to Pol II CTD by in vitro Pull-down (Supplementary Fig. 10a, b). Consistent with the in vivo phase separation pattern, AKAP95 PS-mutant had poorer phase separation in vitro compared with WT protein (Supplementary Fig. 10c). AKAP95 ZF-mutant had a similar phase separation property as WT protein in the absence of RNA. When RNA was added, the size of AKAP95-WT condensates significantly increased, but the size of ZF-mutant condensates remained unchanged (Supplementary Fig. 10d).

Next, we investigated how AKAP95 phase separation augments Pol II CTD condensation. AKAP95 WT protein underwent co-condensation with Pol II CTD in vitro. Like the single proteins’ behavior, co-condensation of AKAP95 PS-mutant and Pol II CTD was weaker than the WT counterpart (Supplementary Fig. 10e). Importantly, addition of RNA enhanced Pol II CTD recruitment into the condensates, as the size of the droplets was increased. However, the size of the droplets formed by AKAP95 ZF-mutant and Pol II CTD was unaffected by the addition of RNA (Fig. 5g). Taken together, our data suggest that phase separation of AKAP95 augments the co-condensation of Pol II CTD. This mechanism may promote further transcription through recruitment of AKAP95 (and Pol II) mediated by nascent transcripts.

Targeting phase separation of AKAP95 attenuates its chromatin binding and pro-oncogenic function
Consistent with the importance of RNA-binding and phase separation for AKAP95 biochemical functions, we found that these two properties were also essential for cancer cell proliferation. AKAP95 WT, but not the ZF- and PS-mutants, were able to rescue the growth defect of MLLr leukemia cells (THP1 and Molm13) caused by the knockdown of endogenous AKAP95 (Fig. 6a and Supplementary Fig. 11a, b). Immunofluorescence staining showed that MLL1 N-terminal fragments (including MLL1T and WT MLL1 breakage N-terminal part) partially colocalized with AKAP95 WT, but not ZF- and PS-mutants in rescued THP1 cells (Fig. 6b). Meanwhile, we carried out ChIP-seq analysis of the exogenous AKAP95 in the rescued THP1 cells. AKAP95 WT had 916 binding sites on the genomic DNA, but the binding intensity of ZF- or PS-mutant was basically abolished at those sites (Supplementary Fig. 11c). The majority of the AKAP95 binding sites (87.76%) were located in gene promoter regions (Supplementary Fig. 11d and Supplementary Data 5). We noticed a significant enrichment of MLL-AF9 targets in the AKAP95 bound promoters/genes (P=0.0017, Supplementary Fig. 11e). AKAP95 binding intensity at MLL-AF9 target sites was higher than that at the rest sites (the difference was not significant, Supplementary Fig. 11f). This data was similar to the ChIP result of endogenous AKAP95 in Hela cells (Fig. 4d).

Since AKAP95 PS-mutant failed to rescue cell growth defect, we sought to target AKAP95 phase separation to inhibit AKAP95-dependent cancer growth. Heat-shock protein HSP70 changed the composition and fluidity of condensates31,32. Recently, HSP70 cofactor HSP40 (J-domain protein) has been repurposed to dissolve intracellular condensates. Here, we tested whether docking AKAP95 to HSP70 system could abolish AKAP95 phase separation, reduce its binding to chromatin, and attenuate its transcription and pro-oncogenic function.

Because AKAP95 is largely disordered and there is no pocket for designing a small molecule, we designed a 30 aa peptide (PI95) based on the conserved region between PKA RIIa and DPY3017, two interacting proteins of AKAP95 (Supplementary Fig. 12a). We purified GST-AKAP95 and mcherry-PI95 as recombinant proteins and confirmed their binding through co-immunoprecipitation (Supplementary Fig. 12b, c). However, a scrambled version of PI95 (PI95 Scr) failed to bind to AKAP95 (Supplementary Fig. 12d). Flag-HA-mcherry-PI95 was also co-immunoprecipitated with Myc-AKAP95 when these two proteins were both overexpressed in 293T cells (Fig. 6c). These results confirmed that PI95 bound to AKAP95 in vitro and in vivo.

Then, we fused PI95 with a conserved J domain (JD, 1–76 aa) of HSP40, which facilitates HSP70 substrate loading and ATP catalysis33. As the control, we used the H32Q mutant, which failed to interact with HSP7034. Immunoprecipitation of AKAP95 showed that HSP70 was hooked to AKAP95 in the presence of JD-PI95 but not H32Q-PI95 (Supplementary Fig. 12e).

Transduction of Hela cells with lentiviral vector expressing exogenous proteins showed that endogenous AKAP95 protein level was unaffected by the presence of either JD-PI95, H32Q-PI95 or JD-PI95 Scr (Supplementary Fig. 12f). However, AKAP95 dissociated from chromatin faster after MNase treatment in the presence of JD-PI95, but not H32Q-PI95 nor JD-PI95 Scr (Fig. 6d). In LacO-U2OS cells, AKAP95-LacI formed puncta with significantly reduced size at the LacO site when JD-PI95 were overexpressed compared with control or overexpression of H32Q-PI95 or JD-PI95 Scr (Fig. 6e). These data indicate that JD-PI95 impaired AKAP95 phase separation.

Using a double luciferase reporter assay, we checked if JD-PI95 impairs AKAP95’s function in activating transcription. Co-transfected G-293T cells showed significantly reduced luciferase signals in the presence of JD-PI95 (Fig. 6f and Supplementary Fig. 12g). When we introduced JD-PI95 into THP1 cells, the transduced cells had remarkably reduced growth rate compared to the control, H32Q-PI95 or JD-PI95 Scr transduced cells in liquid culture (Fig. 6g). We calculated the nuclear concentration of peptide to be approximately 19–38 nM in THP1 cells, which is in the similar range of most small molecular inhibitors (Supplementary Fig. 12h). When the transduced THP1 cells were injected into immunodeficient mice through tail vein, the mice that received JD-PI95 transduced THP1 had significantly less tumor burden than the other three groups (Fig. 6h). qPCR analysis of the transduced cells showed that the static mRNA levels of several MLL-AF9 targets were significantly reduced in JD-PI95 overexpressed (OE) THP1 cells compared to the control (Supplementary Fig. 13a). Pro-seq analysis of JD-PI95 OE THP1 cells showed that there was a huge difference on 916 transcripts between JD-PI95 treated and non-treated cell (Supplementary Fig. 13b). Although the difference of metagene analysis between JD-PI95 and JD-PI95 scr treated cells was not significant, certain MLL-AF9 targets (RUNX2, SMC4, and NEK7) displayed the lowest on-going transcription in JD-PI95 treated cells (Supplementary Fig. 13c). Together, our data suggest that we were able to design a peptide to effectively impair AKAP95 condensation, dampen its transcription-coactivation function, and attenuate its pro-oncogenic activity.

Methods
Study approval
The collection of patient bone marrow was approved by the Ethics Committee of Xiangya Hospital Central South University, and written consent for the research purpose was obtained.
The housing and transplantation procedure were approved by the Institutional Animal Care and Use Committee at the University of Virginia. Housing and operating NCG mice were approved by the Institutional Animal Care and Use Committee at Hunan University.

Mouse transplantation procedures
The wild type and Akap95−/− C57BL/6 mice were maintained at the Animal Research Facility at the University of Virginia. CD45.1+ mice were purchased from Jackson Lab. The NCG (NOD/ShiLtJGpt-Prkdcem26Cd52Il2rgem26Cd22/Gpt) mice were purchased from GemPharmatech Co., Ltd. (Jiangsu, China). Mice were housed at 21–22 °C, 30–70% humidity, with a 12:12-h dark:light cycle.
For primary transplantation, 8- to 12-week-old Akap95−/− or WT mouse bone marrow was sorted against Lin− cells using Lineage Cell Depletion kit (Mitenyi Biotech, cat. 130-110-470). Then, the cells were spin-infected with pMSCV-IRES-GFP (Addgene #20672), pMSCV-MLL-AF9-IRES-GFP (a gift from Dr. Golam Mohi, the University of Virginia) retrovirus or pMIR-FLAG-MLL-AF9 (Addgene #71444). 106 transduced cells were injected into lethal irradiated (9.5 Gy) recipient mice (8- to 12-week-old) through the tail vein. The recipients were monitored afterwards. Disease progression included lethargy, rough coat, and loss of weight. Special care (such as a soft diet) was given when mice were hunched. If the situation became even worse after one or two days, the hunched mice were euthanized, and the day was set as the last day of their survival.
For secondary transplantation, the bone marrow harvest from the moribund primary recipient was sorted for the LGMP population. Then, 4000 LGMP cells were injected into sublethal irradiated (6 Gy) recipient mice.
For competitive transplantation, 1×106 Akap95−/− or WT CD45.2+ bone marrow cells were mixed with CD45.1+ bone marrow cells at a 1:1 ratio and injected into CD45.1+ lethal irradiated recipient mice. Tail blood was harvested every 4 weeks after transplantation for blood profile analysis. The recipients were euthanized at 16 weeks for analysis of the cell constitution in bone marrow and spleens.
For leukemia cell line transplantation, 1×106 THP-1 cells transduced with the JD-PI95 constructs and pLent-LucV5 (expressing the luciferase gene) were resuspended in 100 μl PBS and injected into the tail vein of 8-week-old NCG mice. Recipient mice were injected with D-luciferin (Beyotime Biotech; 3 mg per 20 g) intraperitoneally and anaesthetized with isoflurane. Luminescent images were taken within 20 min after D-luciferin intake using an IVIS Spectrum bioluminescence and fluorescence scanner (PerkinElmer) at the Analytical Instrumentation Center of Hunan University. The recipient mice were taken for imaging at 4 weeks after transplantation, and repeated imaging every week before they got weak. The moribund mice were euthanized at the end.

Cell culture
Mouse bone marrow cells harvested for primary transplantation were cultured in IMDM medium (Gibco) with 20% FBS, 100 μg/mL Pen/Strep, 50 μg/mL SCF, 50 μg/mL Flt3 ligand, 10 μg/mL mouse IL-6, 50 μg/mL Tpo and 50 μg/mL mouse IL-3 (PeproTech). Transformed mouse bone marrow cells were cultured in IMDM medium (Gibco) with 20% FBS and 100 μg/mL Pen/Strep.
Cell lines 293T, THP1, Molm13, K562, Jurkat, HL60 were kept in our lab. MV411, Monomac6 and Kasumi were gifts from Dr. Francine Garrett-Bakelman (the University of Virginia). Hela Flp-In-Trex and U2OS-LacO cells were gifts from Dr. Todd P. Stukenburg (the University of Virginia). Plat-E cells were a gift from Dr. Golam Mohi (the University of Virginia). The cells are authenticated by STR profiling from the commercial vendor. Blood cancer cells were cultured in RPIM1640 (Gibco) with 10% FBS and 100 μg/mL Pen/Strep. 293T, Hela, plat-E and U2OS cells were cultured in DMEM (Gibco) with 10% FBS and 100 μg/mL Pen/Strep.

Knock-in cell construction
To tag the endogenous AKAP95 with Flag-mEGFP, sgRNA (5’-CCTGGTCCATGTCTTCGACGCGG-3’) targeting the N-terminus of AKAP95 was cloned into pSpCas9(BB)-2A-Puro V2.0 (Addgene #62988). A DNA fragment composed of Flag-mEGFP flanked by 800-bp homology arms was inserted into pUC19 vector as donor plasmid. Hela cells were transfected with both the sgRNA construct and the linearized donor plasmid through lipo3000 (Life Technologies). After 4 days of selection against puromycin, cells were sorted on GFP signals on Bigfoot spectral cell sorter (Thermo Fisher Scientific). About 8000 GFP-positive cells were seeded in 6-well plates. Colonies were individually transferred into 96-well plates and then expanded. Validation of the positive KI clones was carried out by genotyping, western blot and imaging. Oligos used in this study are listed in the Supplementary Table.

Virus production and transfection of cells
Retrovirus pMSCV-MLL-AF9-IRES-GFP, pMIR-FLAG-MLL-AF9 or pMSCV-IRES-GFP were packaged in plat-E cells. Lentivirus pLKO.1-shAKAP95, pCDH-MSCV-HA-JD-PI95-puro, pCDH-MSCV-HA-H32Q-PI95-puro, and pCDH-MSCV-HA-JD-PI95scr-puro were packaged in 293T cells with the envelope plasmids of psPAX2 and pMD2.G. The virus supernatant was concentrated 30-fold by PEG8000 precipitation, then aliquoted and stored at −80 °C.
For blood cells transduction, 1×106 cells were transduced with 200 μL of concentrated virus by spin infection at 1000×g for 1.5 h. For attached cells transduction, cells grown in one well of a 6-well plate were infection with 200 μL of concentrated virus. Ten to twelve hours later, cells were changed with fresh medium. Twenty-four hours after transduction, cells were subjected to selection. Sometimes, double infections were required for blood cells.

Antibodies
Antibodies used include. WB (antibodies were generally 1:2000 diluted): rabbit anti-AKAP95 (Bethyl Laboratories, A301-061A); mouse anti-GAPDH (Millipore MAB374); rabbit anti-MLL1 (NT86) (Bethyl Laboratories, A300-086A); mouse monoclonal anti-FUS (H-6) (Santa cruz, sc-373698); mouse monoclonal anti-flag (Yeasen Biotech, 30503ES); mouse monoclonal anti-GST (Yeasen Biotech, 30901ES); mouse monoclonal anti-HA (Yeasen Biotech, 30704ES); mouse monoclonal anti-His (Yeasen Biotech, 30401ES).
ChIP, IP, and IF (antibodies were generally 1:500 diluted): Mouse anti-flag magnetic beads (Selleck, B26101); rabbit polyclonal anti-Pol II RBP1 (N-20) (Santa cruz, sc-899); rabbit monoclonal anti-Pol II Ser2P (Cell signaling, #13499); rabbit monoclonal anti-H3K4me3 (Millipore 05-745R); rabbit polyclonal anti-H3K27me3 (Millipore 07-449); rabbit polyclonal anti-H3K27Ac (Abcam ab4729); anti-H3K4me1 (Abcam ab8895); rabbit anti-MLL1 (D2M7U, Cell signaling, #14689); Alex Fluor-555 donkey anti-rabbit IgG (Thermo Fisher Scientific, A-31572).
FACS (antibodies were generally 1:1000 diluted): APC-mouse Lin-cocktail (BD, 51-9006309); anti-mouse CD16/32 Fc block (Biolegend, 101301); PE-anti-mouse c-Kit (BD, 553355); PE-Cy7-anti mouse Sca-I (BD, 558162); BV711-anti-mouse Mac-1 (Biolegend, 101241); BV421-anti-mouse Gr-1 (Biolegend, 108433); BV711-anti-mouse CD16/32 (Biolegend, 101337); BV421-anti-mouse CD34 (Biolegend, 152207); APC-anti-mouse B220 (Biolegend, 103211); Percp-Cy5.5-anti-mouse CD3e (Biolegend, 152311); FITC-anti-mouse CD45.2 (Biolegend, 109806); PE-anti-mouse CD45.1 (Biolegend, 110707); BV510-anti-mouse CD45.1 (Biolegend, 110741).

Flow cytometry and cell sorting
Single-cell suspensions were prepared from bone marrow, spleen, or peripheral blood. Red blood cells were removed using ACK lysis buffer.
The following panel of surface markers was used for separating individual population: LSC (GFP+Lin−c-kit+Mac-1+Gr1+); LGMP (c); LSK (Lin−c-kit+Sca-I+); CMP (Lin−c-kit+Sca-I−CD34+CD16/32−); GMP (Lin−c-kit+Sca-I−CD34+CD16/32+); MEP (Lin−c-kit+Sca-I−CD34−CD16/32−).
FACS analysis was performed on LSR Fortessa (Becton Dickinson), and data were analyzed using FlowJo software (TreeStar).
FACS sorting was performed on LSR Aria II (BD). MLL-AF9 transduced BM were sorted for RFP+Lin−c-Kit+ before being used for the CFC assay. For sorting LGMP cells, BM cells from moribund mice were sorted against GFP+Lin−c-Kit+CD34+CD16/32+.

CFC assay
MLL-AF9 transduced Lin− cells were grown in M3234 methyl Cellulose media (Stem cells) supplemented with 10 μg/mL IL-3, 10 μg/mL IL-6 and 20 μg/mL SCF (PeproTech). Colony numbers were counted 7 to 10 days later. One thousand cells were re-plated in the next round, and this process was repeated 4–5 times.

FRAP
For live-cell imaging of the endogenous Flag-mEGFP labeled AKAP95, Hela cells were grown on 35-mm glass-bottom dishes (Nest Biotech). AKAP95 foci were captured on Zeiss LSM980 confocal microscope with the Airyscan detector. FRAP assay was performed as previously described. For other fluorescence imaging, transfected 293T cells or U2OS cells were observed under Zeiss observer Z1 with 63× oil lens.

Cell fractionation
Stable expression of AKAP95 (WT, ZF- or PS-mutant)-GFP Hela cell lines were established in Hela Flp-In-Trex cells following manufacturer’s instructions. To test the peptide effect, Hela KI cells were transduced with pCDH-alone, pCDH-MSCV-HA-JD-PI95-puro, pCDH-MSCV-HA-H32Q-PI95-puro or pCDH-MSCV-HA-JD-PI95scr-puro lentivirus. After selection, 4×107 cells were collected, washed with PBS and resuspended in 1.5 mL of Buffer A (10 mM HEPES [pH 7.9], 10 mM KCl, 1.5 mM MgCl2, 0.34 M sucrose, 10% glycerol, 1 mM DTT, protease inhibitor cocktail, and 0.1% Triton X-100). The cells were incubated on ice for 8 min, and nuclei (fraction P1) were collected by centrifugation at 1300×g, 4 °C for 5 min. The P1 nuclei were washed once in buffer A and resuspended in 1.5 mL of buffer B (3 mM EDTA, 1 mM DTT and protease inhibitor cocktail), and 0.3 mL of the suspension was saved for WB. The rest suspension was divided into two parts, one added RNase (3 μL, 100 μg/mL final) and one not. After incubation on ice for 30 min, the soluble nuclear fraction (S2) and insoluble fraction (P2) were separated by centrifugation at 1700×g, 4 °C for 5 min. The P2 was washed once with buffer B and resuspended in nuclease digestion buffer (10 mM Tris, 10 mM KCl, and 1 mM CaCl2), then divided into 3 portions (0.2 mL each). One portion was immediately centrifuged to separate the chromatin-associated fraction (S3) and insoluble fraction (P3). The other two portions were added 0.4 μL of MNase (4000 U/mL, New England BioLabs). After incubation at 37 °C for 2 or 5 min, the suspension was centrifuged at 1700×g, 4 °C for 5 min to get S3 and P3 fractions. Equivalent portion of supernatants or pellets was denatured with SDS loading buffer and subjected for western blot.

Immunostaining and imaging
Hela Flp-In-Trex AKAP95 (WT, ZF- or PS-mutant)-GFP cells were further subjected to knockdown of endogenous AKAP95 by lentiviral pLKO.1 vector. Cells were grown on the coverslip, fixed with 4% formaldehyde, and permeabilized with 0.5% Triton X-100. For suspension cells, THP1 cells rescued with pCDH-MSCV-AKAP95 (WT, ZF- or PS-mutant)-GFP lentivirus were cytocentrifuged to glass and fixed. Primary and secondary antibodies were diluted at 1:500. Images were taken on a Zeiss LSM980 confocal microscope with the Airyscan detector.

Co-immunoprecipitation assays
293T or Hela cells transfected or transformed with indicated constructs were harvested and lysed in BC300 (50 mM Tris-HCl pH 7.4, 300 mM KCl, 20% glycerol, 0.2 mM EDTA) with 0.1% NP40, 1 mM DTT, and protease inhibitor cocktail (Roche, 4693159001). Lysates were incubated with the anti-Flag antibody (Selleck) and washed with lysis buffer. Bead-bound proteins were resolved by SDS-PAGE and detected by immunoblotting.

Double luciferase reporter assay
G-293T cells were transfected with pcDNA5-FH-AKAP95, or ZF-/PS-mutant, together with pGal4-VP16 and pRL. To test the JD-PI95 effect, G-293T cells were co-transfected with pcDNA5-FH-AKAP95 and pcDNA5-HA-JD-PI95 or pcDNA5-HA-JD-PI95Scr in the presence of pGal4-VP16 and pRL. Forty-eight hours later, cells were lysed and detected with a double luciferase reporter kit (Promega). Transcription efficiency was present as firefly luciferase signals normalized by Renilla luciferase signals.

Pol II CTD cloning
Pol II RPB1 CTD were cloned with primers (F: 5’-CGCGGATCC cgcaccacgtccaatga-cattg-3’; R: 5’-CGCGTCGAC gggtgaggttgggctgtagctg-3’) and Hela cDNA as template. RT-PCR products were inserted into the pET28a vector to make pET28a-His-mch-Pol II CTD. Several clones were sent to Sanger sequencing. The plasmid harboring aa 1356-1767 (including 23 heptapeptide repeats) was used for protein purification.

Protein purification and in vitro immunoprecipitation
Plasmids pET28a serials or pGEX-AKAP95 were transformed into E. coli BL21 Star (DE3) (Yeasen Biotech). Bacterial culture at OD600 of 0.6 was induced with 0.4 mM of IPTG (Yeasen Biotech) for 5 h at 25 °C. For purification of 6×His-tagged proteins, bacterial pellets from 500 ml IPTG-induced culture were resuspended in 6 mL of lysis buffer 50 mM Tris-HCl, pH 7.3, 450 mM NaCl, 10 mM imidazole, 1× protease inhibitors (Roche) and lysed by sonication. After centrifugation, the supernatant was incubated with 1 mL of pre-equilibrated HisSep Ni-NTA Resin (Yeasen Biotech, 20502ES) for 1–2 h at 4 °C, washed with wash buffer (50 mM Tris-HCl pH 7.3, 450 mM NaCl, 20 mM imidazole), and eluted with 0.5 mL elution buffer (50 mM Tris-HCl pH 7.3, 450 mM NaCl, 250 mM imidazole) 5 times. For purification of GST-tagged proteins, bacterial lysates were incubated with GSTSep Glutathione agarose beads (Yeasen Biotech, 20507ES) and washed 3 times with wash buffer (50 mM Tris-HCl, pH 7.3, 450 mM NaCl). Then, the GST-AKAP95-contained beads were incubated with the His-tagged protein solution at 4 °C for 3 h. After a thorough wash, the beads were resuspended in SDS-loading buffer and subjected to immunoblotting. Purified proteins were also validated by Coomassie blue staining.

Estimation of peptide concentration
By immunoblotting of lysates from a known number of cells along with the purified and quantified Flag-JD-PI95 protein, and based on the nuclear volume of 220 fl of HeLa cells, we calculated the concentration of peptide to be approximately 19–38 nM in THP1 cells.

In vitro phase separation
Image-based phase separation was carried out as previously described. Briefly, purified proteins were stored in high salt concentration and without PEG, and were diluted using a “condensation buffer” into a final condition of indicated protein concentration, 150 mM NaCl and 7.5% PEG8000, 50 mM Tris-HCl, pH 7.3, 10% glycerol, 1 mM DTT. AKAP95 and Pol II CTD co-condensation was carried out by mixing the two proteins for 1–2 mins then diluting the mixture with condensation buffer. Total Hela cell RNA was added to the protein solution before the condensation buffer. Protein mixtures were added to a homemade flow chamber comprised of a glass slide sandwiched by a coverslip with one layer of double-sided tape as a spacer. Images were taken on a Zeiss Axio Observer Z1 microscope with a 63× oil lens. Fluorescent and differential interference contrast (DIC) microscopy images were taken.

RNA extraction and RNA-seq analysis
RNA extraction was done by the Trizol method. RNA integrity was confirmed by gel electrophoresis. qPCR was carried out with SYBR green and quantified with 2−ΔΔCt method. For RNA-seq library preparation, mRNA was enriched by polyA+ selection, converted to cDNA, labeled with adapters and barcodes with NEBNext Ultra II Directional RNA Library Prep Kit for Illumina (New England BioLabs, E7760). The 75 bp pair-end sequencing was performed using the Next-seq (Illumina).
RNA-seq reads were aligned to the human genome assembly GRCH37/hg19 or the mouse genome assembly GRCm38/mm10 using STAR. RNA-seq counts were annotated using RSEM. Read counts were normalized to TPM (transcripts per million reads). Differentially expressed genes were calculated using DE-seq2. Significant DEGs were selected at the thresholds of adjusted P value < 0.05 and |fold change| > 2 if otherwise described. Gene ontology and pathway analysis were conducted using DAVID v6.8 (https://david.ncifcrf.gov/summary.jsp) and GSEA. Heatmaps of differentiated genes between treatments were plotted with the R package ggplot2.

ChIP and ChIP-seq analysis
ChIP was carried out as previously described with individual antibodies. The immunoprecipitated DNA was used for ChIP-seq library preparation with the NEBNext Ultra II DNA library Prep Kit for Illumina (New England BioLabs, E7645). Libraries were sequenced using the Next-seq sequencer (Illumina) in single-end 75 bp mode.
ChIP-seq reads were aligned to the human genome assembly GRCH37/hg19 or mouse genome assembly GRCm38/mm10 using BWA. Sam files were converted into bam files using Samtools. MACS2 was used to call peaks under the FDR threshold of 0.01. For H3K4me1, 3 and H3K27ac ChIP-seq data, SICER258 was applied to call broad peaks (islands) with default parameters. AKAP95 ChIP-seq peaks were called with MACS software (version 1.4.3). AKAP95 binding sites were annotated with the Homer software as promoter (1.5 kb upstream of transcription start site), 5’ UTR, exon, intron, 3’ UTR, small noncoding RNA, TTS (1 kb downstream of transcription terminal site) and intergenic region.
Hela cell enhancers were referred to previously reported information. ChIP-seq read density in these regions was calculated and plotted with the DeepTools software. For the PolII and Ser2P, each mapped bam file was normalized with the counts per million mapped reads method and plotted with the Deeptools software. Motif enrichment analysis in AKAP95 ChIP-seq was performed using HOMER software to identify the transcription factor characterized by a motif enriched with the most significant P-value. The overlapping peaks between ChIP and CLIP were determined using the MergePeaks function of the HOMER software with an interval distance of 5 kb.

CLIP and CLIP-seq analysis
Cells grown in 10-cm dishes were crosslinked with 600 mJ/cm2 of 254 nm UV light. The nuclei were prepared by incubating cells in hypotonic buffer (10 mM HEPES [pH 7.9], 10 mM KCl, 1.5 mM MgCl2, 0.34 M sucrose, 10% glycerol, 1 mM DTT, protease inhibitor cocktail, 0.1% Triton X-100 and 400 U/mL RNase inhibitor). Isolated nuclei were resuspended in lysis buffer (1X PBS, 0.5% NP-40, 0.5% sodium deoxycholate, 0.1% SDS and 400 U/mL RNase inhibitor). After brief sonication, the lysate was centrifuged at 1300×g, 4 °C for 10 min. The supernatants were incubated with 40 μL pre-equilibrated anti-flag beads (Selleck) at 4 °C overnight. Then, the beads were washed twice with cold CLIP lysis buffer and two more times with high salt wash buffer (5X PBS, 0.5% NP-40, 0.5% sodium deoxycholate, 0.1% SDS and 400 U/mL RNase inhibitor). The protein-RNA complex-bound beads were washed four times with PNK buffer (50 mM Tris pH 7.4, 10 mM MgCl2, 0.5% NP-40). The RNAs were partially digested with MNase (New England BioLabs, 1:105 diluted) at 37 °C for 10 min. The reaction was stopped by PNK-EGTA buffer (PNK buffer with 2 mM EGTA). Then the beads were washed twice with PNK buffer. To dephosphorylate the RNA, the beads were treated with CIP (New England BioLabs) for 10 min at 37 °C. After two more washes with PNK buffer, the pre-adenylated 3’ linker (rAppCTGTAGGCACCATCAAT-NH2, Beyotime Biotech, R0700S) was ligated with truncated T4 RNA ligase 2 (New England BioLabs) at 16 °C overnight. Then the non-ligated 3’ linker was washed away with two washes of CLIP lysis buffer and two washes of PNK buffer. The RNAs were then phosphorylated by T4 PNK (New England BioLabs) for 10 min at 37 °C. To elute the protein-RNA complex, the samples were treated with Proteinase K (50 mM Tris, pH 7.4, 150 mM NaCl, 0.5% SDS, and 20 mg Proteinase K) for 30 min at 37 °C. The RNAs were purified and ligated with 5’ RNA adapter (GUUCAGAGUUCUACAGUCCGAC, Sangon Biotech) by T4 RNA ligase (New England BioLabs). Then the RNAs were reverse transcribed by Superscript III (Life Technologies) with RT primer (CTGTAGGCACCATCAAT, Sangon Biotech) and amplified for 20 cycles with Q5 DNA polymerase (New England BioLabs) (Primer_Forward: GTTCAGAGTTCTACAGTCCGAC; Primer_Reverse: CTGTAGGCACCATCAAT, Sangon Biotech). Library index sequence was introduced by PCR with index primers (Forward (SR primer): AATGATACGGCGACCACCGAGATCTACACGTTCAGAGTTCTACAGTC CGAC, Reverse: CAAGCAGAAGACGGCATACGAGATCGTGATGTGACT GGAGTTC CTGTAGGCACCATCAAT) (the underlined hexamer indicates Illumina index sequence, Sangon Biotech) for eight more cycles.
AKAP95 binding sites were annotated as promoter (1 kb upstream of transcription start site), 5’ UTR, exon, intron, 3’ UTR, small noncoding RNA, TTS (1 kb downstream of transcription terminal site) and intergenic region. Alternative splicing isoforms were analysed as previously described with MISO software with its version 2.0 annotation of all known alternative splicing events according to the online documentation https://miso.readthedocs.io/en/fastmiso/.

Pro-seq signaling
Pro-seq library construction was performed as previously described. Libraries were sequenced using the Next-seq sequencer (Illumina) in single-end 75 bp mode.
Sequence reads were aligned to the human genome assembly GRCH37/hg19 using BWA. Sam files were converted into bam files using Samtools55. MACS2 was used to call peaks under the FDR threshold of 0.01. To generate the coverage of the aligned sequence reads, the bam files were converted to BEDPE files using BEDtools. Only the 5′ end of mate 1 reads were kept into a bed file and converted into bedGraph files using “bedtools genomecov -bg –strand”. The raw read counts in bigWig coverage tracks were normalized by sequencing depth (counts per million mapped reads). The Pro-seq metagene plot was generated with the deeptools software.

Statistics
Experimental data are presented as the mean ± s.d. of three independent experiments unless otherwise noted. Statistical analysis was carried out by two-sided unpaired Student’s t test (for two-sample comparison), log-rank test (for survival analysis), or Fisher’s exact test (for gene overlap), Mann–Whitney U Test (for omics analysis) as indicated in figure legends. Statistical analysis was performed using Prism, Excel or Python. A P value of less than 0.05 was considered significant. Statistical significance levels if otherwise described are denoted as follows: *P < 0.05, **P < 0.01, ***P < 0.001 and ****P < 0.0001.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "In this paper, the authors studied the function of AKAP95, an established RNA binding protein (RBP) and transcriptional\ncofactor, in regulating oncogenic effects of MLL-fusion (MLLr) proteins in AML. First, authors reported that AKAP95 is over-\nexpressed in MLL-r AML and AKAP95 loss slowed the proliferation of MLLr AML in vitro and in vivo. Authors also used\nRNA-seq, ChIP-seq and CLIP-seq to show that AKAP95 associates with both target genes and target transcripts to\nmodulate the transcriptional levels. Using the cell fractionation and cell imaging experiments, authors further demonstrated\nthat AKAP95 relies on the RNA binding functon(within a zinc finger domain) and phase separation functon(within IDR; PS\nmutation of Tyr to Ser in aa 101-210) to tightly bind onto chromatin targets. Interestingly, PS mutant failed to phase separate\nand also failed to interact with MLL1-T and had a weaker co-condensation with RNA POL II CTD. Lastly, authors proposed\nto use heat shock protein to disrupt phase separation property of AKAP95; and on this line, they used a JD-PI95 fusion to\ntreat MLLr AML. Preliminary data showed the effects of JD-PI95 in vitro and in vivo. Overall, this work presented interesting\nfindings and studied a potentially important phenomenon related to phase separation, gene regulation and leukemia\ndevelopment. But some shown datasets were not carefully analyzed. Writing requires extensive editing. I have a few\ncomments as listed below.\nMain comments.\n(1) This work used RNA-seq to define the differentially expressed genes after AKAP95 loss. But whether these genes are\nupregulated or downregulated is not specified. This refers to Figure 3 such as 3B and 3C. Authors seem to suggest\ndownregulation in Fig 3C? The detected changes need to be verified with other methods such as qPCR.\n(2) What is the molecular basis underlying the AKAP95 IDR interaction with MLL1-T (and maybe POL II CTD)?\n(3) In the Fig S9A rescue experiment, the PS mutant is expressed at the lower level than WT or ZF mutation. This raises a\nconcern. Also, authors only used THP1 cells in rescue. Other MLLr cell lines shall be used to confirm the findings.\nAnd authors shall use the cells in Fig S9A rescue experiment for cell imaging of condensation of AKAP95 with MLLr and\nRNA POL II (like Figure 4B).\n(4) The studies using JD-PI95 were incomplete. Peptide inhibitor is known to be hard to deliver into cells or mice and\nprobably is less stable. The concentrations of JD-PI95 used in Figure 6 are not specified. A PI95 scramble control shall be\nused as an additional control for the JD-PI95 fusion. What are the effects of JD-PI95 versus control on target gene\nexpression or binding of AKAP95:MLLr at target genes?\n(5) Grammar related issues and typos need to be addressed. There are many issues in the Introduction and Discussion\nsections.\nMinor comments.\n(1) More datasets of MLLr versus non-MLLr human patient datasets shall be used to analyze AKAP95 expression.\n(2) More MLLr cell lines such as MOLM13 shall be tested in Figure 1.\n(3) Are motifs shown in Figure 4D related to MLLr?\n(4) In Fig S9G, why did authors use MDA-MB-231 (a triple negative breast cancer cell line)?", "reviewer_2": "The manuscript by Yan and colleagues studies the potential role of AKAP95 (aka AKAP8) in transcriptional control. The\ninvestigators use a combination of genetics and genomics to make the argument that AKAP95 is not only critical for MLL\nfusion protein action, but also for RNA polymerase functions through inducing condensate formation. The authors have\ngenerated a lot of data that indicates that AKAP95 is not required for normal cellular functions or for hematopoietic stem and\nprogenitor cell function, even in the face of a bone marrow transplant. These results suggest that AKAP95 is not required for\nthe majority of transcriptional control, even under stress conditions when cells must rapidly cycle to replenish the bone\nmarrow. Nevertheless, when comparing cells with or without AKAP95, there were changes in about 5% of the transcripts,\nwhich likely describes the change in cell phenotype.\nThe challenge in trying to establish that an RNA binding protein is regulating transcription is determining whether the\n“chicken or the egg” comes first. That is, is RNA polymerase regulating AKAP95 condensate formation by making a nascent\nRNA that recruits AKAP95 to chromatin or is AKAP95 regulating transcription by binding to DNA or to RNA Polymerase?\nUnfortunately, the genetic approaches employed are too slow to establish cause and effect relationships, as even the\nshRNAs take a couple of days to inhibit AKAP95. However, the investigators have a system in which they could integrate a\ndegron tag into the endogenous alleles of AKAP95, which would allow rapid degradation of AKAP95. A short time course of\ndegradation (0, 15’, 30’, 60’) coupled with PRO-seq would define the changes in nascent transcription and determine if\nAKAP95 is required for transcription initiation and/or elongation. Without a doubt, this would be a lot of work, but it is\nnecessary to prove the conclusions that the authors are trying to make. Currently, the work suggests that AKAP95 is not\ncritical for RNA polymerase functions, but might contribute to the fine tuning of some genes, perhaps even some that are\nimportant for MLL fusion protein action.\nMajor Comments:\n1) The work relies heavily on shRNA knockdowns that trigger inflammation and have other off target effects. It would be\nuseful to confirm the key findings using CRISPRs and to compare the data with those in the DEPMAP.\n2) ChIP-seq data are not convincing as shown. The scales on the IGV screen shots are very small, which implies very low\nsignal over the noise. This should be benchmarked to the signal of RNA Pol II to give the reader a comparison. It really looks\nlike AKAP95 just binds nascent RNA, and it is getting crosslinked to DNA via its recruitment by RNA or through RNA\npolymerase. That is, transcription is regulating AKAP95 rather than AKAP95 regulating transcription. This could be tested by\ndegrading RNA polymerase using a short treatment with  -amanintin prior to ChIP-seq analysis, which would establish that\nAKAP95 binds to the promoters identified.\n3) If one accepts the ChIP-seq data, then only 29 genes showed both differential regulation, ChIP signal and CLIP signal,\nyet all RNA Pol II was affected by the expression of the mutants (Fig. 5E). It seems likely that this is just due to the cells\ngrowing more slowly (i.e., sick cells) rather than an interaction with chromatin.\n4) The genomic analysis in Figures 3-4 don’t hold together well. If AKAP95 is at 3348 promoters (roughly 1/3 of the\nexpressed genes), why are so few genes affected by knockout of the gene? The most common artifact of ChIP-Seq is a\nsmall signal at promoters, but if the signal is real, why is there no effect on H3K4me3 levels at MLL fusion protein targets\n(Fig. 3E)? Moreover, there were large changes in H3K27ac genome wide (Fig. 3D), which implies that all genes were\nrepressed to some degree?\n5) The PRO-seq data indicates no effect of AKAP95 on nascent transcription, but it is a very unusual plot in that there is as\nmuch antisense transcription as sense and there is little divergence between the WT and the mutants. The histograms\nshown are also quite confusing in that they show both sense and antisense transcription at -1000 bp from the TSS. The\nauthors should consider showing some screen shots that show a possible defect in nascent transcription more clearly.\n6) If the fusion peptide truly inhibits condensate formation, then treating cells with the peptide and performing a short time\ncourse (0, 15’, 30’, 60’) of PRO-seq should define the role of AKAP95 in transcription control. It would be expected to cause\na collapse of RNA polymerase at AKAP95-regulated loci.\nMinor:\n1) The authors might want to consider breaking the work into two manuscripts. The MLL story doesn’t really integrate well\nwith the HeLa and 293 cell work, as the is presumably not much overlap in regulated genes. There is a lot of data here, but it\ndoesn’t fit together in a very coherent manner.\n2) The motif analysis doesn’t add anything to the story, as these are just binding sites associated with promoters.\n3) It would probably be prudent to avoid calling myeloid progenitor cells LSCs unless formally proven to be LSC through\nlimiting dilution analysis.", "reviewer_3": "In this study, Yan et al. investigate how the RNA binding protein AKAP95 contributes to MLL-rearranged (MLLr) leukemia\nthrough both transcriptional regulation and RNA splicing. This work is a followup on the authors’ previous manuscript\npublished in Nature Cell Biology where they study AKAP95 condensate regulation and oncogenic function in breast cancer\nmodel. Here the researchers found that AKAP95 is upregulated in MLLr leukemia compared to other types of acute myeloid\nleukemia and is essential for leukemia development but dispensable for normal blood cell formation. Mechanistically,\nAKAP95 uses both its RNA-binding ability and its capacity to undergo phase separation (form liquid-like droplets) to bind to\nchromatin and regulate gene expression. The protein co-localizes with MLL fusion proteins and helps recruit RNA\npolymerase II to activate transcription. To target AKAP95 therapeutically, the researchers designed a peptide that disrupts its\nphase separation by recruiting the cell's protein quality control machinery (HSP70). This peptide successfully reduced\nAKAP95's ability to regulate transcription and impaired cancer cell growth, suggesting a potential new therapeutic strategy\nfor MLLr leukemia.\nAlthough there is a large set of work that will be of great interest there are some general concerns about the internal logic of\nthe study:\n1. Most of their mechanistic studies are performed in HELA cells or 293T cells and thus the direct relevance in leukemia is\nnot clearly defined.\n2. It is unclear from the mechanistic studies why these are specifically MLL-dependent. Also, it is not clear that their\nmechanisms are directly related to MLL-associated targets. Importantly, only 11 out of 128 MLL-AF9 targets are impacted\nand thus why are those targets special. Moreover, this does not make sense within the context of RNA polII transcriptional\nregulation.\n3. Is AKAP95 also show specificity for other leukemias driven by NPMc or NUP98? These leukemias are thought to be\ndysregulated transcriptionally similar to MLL fusions.\n4. Does the peptide delay leukemogenesis beside reduce disease burden?\n5. Does the peptide also have MLL specific requirement?\n6. Is this relevant to primary leukemia samples? Use of some primary AML patient material would strengthen their findings.\nDepletion or use of the peptide in AML patients plus examining their targets in patient cohorts.\nSome additional, more specific points to be addressed are listed below:\nMajor points\na. Figure 1:\ni. Please provide protein evidence for differential AKAP5 expression across these cell lines. Is it comparable to normal\nCD34+ cells?\nii. 1C, its unclear what is being compared here.\niii. 1D Is reduced growth attributed to apoptosis? or increased differentiation?\nb. Figure 2: there is a lack of transition between the experiments. Needs to be structured better.\ni. 2D: Morphological analyses should be supported by immunophenotypic evidence for myeloid markers.\nii. Lines 138-139: where are these RFP positive cells being derived from? There are no RFP+ cells introduced in this\nexperiment so far.\niii. Line 140: unclear which plating is being referred to here: related to Figure 2d and 2e or Supplemental figure 2C.\niv. Figures 2F-2G: please provide a guide that these experiments are related to secondary Tx of LGMP derived from primary\nrecipients.\nc. Figure 3:\ni. Panel A: unless specific DEG are being highlighted in the heat map its not informative. Please label the colorkey. What is\nthe threshold?\nii. Line 162-163: dysregulated is vague, could suggest up-or-downregulated. And which group?\niii. Panel B: Indicate if these are GO processes for DEG up or down in WT MA9\niv. Lines 165-166 and panels D and E. Authors initially show global enrichment plots for H3K27Ac and switch over to\nH3K4Ac in the trackplots in panel E. Although both are associated with active transcription, they each denote specific\nproperties. Additionally, they claim differences in H3K4me3, but the trackplots do not support this claim? Were there any\ndifferences in the enrichment for H3K27ac on the MLL-AF9 targets?\nd. Figure 4 and related Supplemental Figure 5\ni. Given the poor image resolution in panels S5D and 4B , the foci and colocalization are not clear.\nii. Line 181 provide reference for “AKAP95 interacts with MLL-fusions”\niii. The authors endeavor to provide a mechanistic understanding of AKAP5 by performing CHIP-seq and CLIP-seq to\nsuggest DNA and RNA-binding properties. Although informative, its unclear if these mechanisms play a role in regulating\nMLL-AF9 targets, specifically, their nascent transcription and/ or mRNA stability.\ne. Figure 5 and related supplemental Figures 7 and 8\na. Please indicate in the text what “P1” stands for.\nb. Panels D: Label which enrichment plots are being shown here?\nc. Panel F: Is there an overlap between the Pro-seq occupancy with the MLL-AF9 target genes identified in Figure 3?\nd. Panels 8E and 8D: is not in order with the text.\ne. Panel 8D: poor image resolution\nf. Figure 6I: Please label what the barplots indicate.\nMinor points\na. Inconsistent formatting across figure legends (e.g., some use full sentences while others use fragments)\nb. Some panels aren't fully explained (especially in supplementary figures)\nc. Statistical information could be more consistently presented.\nd. Scale bars are sometimes mentioned in text but not clearly visible in figures.\ne. Some abbreviations are used before being defined.\nf. Panel labels (A, B, C, etc.) aren't always clearly linked to their descriptions.\ng. Figure 1 legend, which could be clearer about the experimental setup and controls.\nh. Figure 5 legend, which has complex descriptions of multiple experiments that could be better structured.", "reviewer_4": "In this manuscript, Yan et al. report that the co-condensation of AKAP95 and MLLr within the nucleus is essential for MLLr\nleukemogenesis. Mechanistically, they found that AKAP95 activates transcription by interacting with nascent RNAs on\nchromatin and recruiting Pol II through phase separation. Disrupting the co-condensation between AKAP95 and MLLr with\npeptides can inhibit tumor growth. These findings are intriguing and potentially important for therapeutic applications;\nhowever, the following concerns need to be addressed to meet the publication criteria:\nThe writing is poor and requires thorough polishing. For example, the title does not adequately capture the full scope of the\nmanuscript. The abstract and many other sections also need further modification.\nFor the upregulations or downregulations mentioned in the manuscript, it would be beneficial to provide the fold-change\nvalues. For instance, in Figure 1C, the upregulated fold appears to be subtle.\nIn Figure 1D, the authors should perform a rescue experiment to determine whether the observed cell proliferation effects are\ndirect or the result of off-target or secondary effects.\nIn Figure 3E, it seems that the H3K4me3 ChIP signal does not change in the two snapshots. If there are changes, the\nauthors need to quantify them.\nFor Figure 4B, the figure quality is poor and contradicts their claims. The phase separation of AKAP95 and MLL1T is not\nvisible, as no puncta or foci can be observed.\nIf AKAP95 regulates transcription by binding to nascent RNA, the authors should explain why the ChIP targets and CLIP\ntargets show minimal overlap (29 out of 556). Additionally, the CLIP is mislabeled as RIP in Figure 4F."}, "author_response": "Response to the reviewer’s comments\nNCOMMS-24-66722\nPhase separation of AKAP95 regulates oncogenic MLL-fusion driven transcription and its\nmodulation for cancer therapy\nWe thank the reviewers for the insightful comments and suggestions, and have made an earnest\nattempt to address all of these comments with relevant experiments, analyses, and more in-depth\ndiscussions. We believe that essentially all of the comments have now been appropriately\naddressed in the revised manuscript. The most significant revisions are:\n(1) We did the following improvements to make the mechanism of transcriptional condensation\nand the mechanism of MLLr leukemogenesis coherent:\na) We provided more bioinformatic data, added fresh patient sample data, and reanalyzed\nmouse MLL-AF9 leukemia data to strengthen AKAP95 relevance to MLLr leukemia.\nb) We reanalyzed the previous omics data, and found MLL-AF9 targets (Olsen et al., Mol\nCell, 2022, PMID: 35245435) were enriched in AKAP95 ChIP binding promoters/genes\n(although obtained from Hela cells). Moreover, AKAP95 ChIP binding intensity at MLL-\nAF9 targets were significantly higher than other binding sites. The degree of down-\nregulation of AKAP95/MLL-AF9 joint targets was significantly greater than that of other\nAKAP95 targets when AKAP95 was loss. All these together indicate that AKAP95 have\na preference for regulating MLL-AF9 targets.\nc) We carried out new ChIP-seq analysis of exogenous AKAP95 in THP1 cells (rescue\nassay), and found MLL-AF9 targets again were enriched in the exogenous AKAP95\nChIP binding promoters/genes, which echoes that AKAP95 and MLL1T had partial co-\nlocalization in THP1 cells.\nd) We provided the evidence that static and on-going transcription of several MLL-AF9\ntargets were significantly reduced when AKAP95 phase separation targeting peptide\nJD-PI95 was added into the culture of THP1 cells.\n(2) We have refined our work model of AKAP95 condensates regulating MLL-fusion driven\noncogenic transcription.\na) To strengthen the co-condensation of AKAP95 and MLL1T, we provided the evidence\nthat MLL1N (including MLL1T and wildtype MLL1 N-terminal part after cleavage)\npartially co-localized with exogenous AKAP95-WT in THP1 cells, but not ZF- or PS-\nmutant, by immunostaining. Moreover, we added bioinformatic analysis of the\nbiochemical parameters of AKAP95 fragments and MLL1T to support their biophysical\nactivities.\nb) Through reanalyzing omics data and reorganizing figures, we proposed “a two-layer\nmechanism” for how AKAP95 regulates MLL-fusion driven oncogenic transcription :\nThrough binding to nascent RNA and phase separation, AKAP95 augments Pol II\ninvolved transcription machinery condensation, to enhance transcription; Partial co-\nlocalization of AKAP95 and MLL1T at the promoters of MLL-AF9 targets renders MLL-\nfusion leukemia is especially dependent on AKAP95 expression.\n(3) We completed the condensate-modifying assay by including another peptide control.\n(4) We have changed the title to “AKAP95 condensates regulate transcription and can be\ntargeted in MLL-fusion driven oncogenesis”\nAll major changes are marked in blue type throughout the manuscript including figure legends.\nThe revised manuscript includes 6 figures, 13 supplementary figures, 6 tables. Our response to\neach point raised by the reviewers is included in blue-highlighted text following each point, and\nsometimes with inserted figures R1-R3 for reviewers to evaluate (not included in the manuscript).\nWe sincerely hope that the reviewers and editors will find our responses satisfactory, and that the\nrevisions now render this paper acceptable for publication in Nature Communication.\nReviewer #1 (Remarks to the Author): Expert in phase separation, ChIP-seq, CLIP-seq and\ncancer\nIn this paper, the authors studied the function of AKAP95, an established RNA binding protein\n(RBP) and transcriptional cofactor, in regulating oncogenic effects of MLL-fusion (MLLr) proteins\nin AML. First, authors reported that AKAP95 is over-expressed in MLL-r AML and AKAP95 loss\nslowed the proliferation of MLLr AML in vitro and in vivo. Authors also used RNA-seq, ChIP-seq\nand CLIP-seq to show that AKAP95 associates with both target genes and target transcripts to\nmodulate the transcriptional levels. Using the cell fractionation and cell imaging experiments,\nauthors further demonstrated that AKAP95 relies on the RNA binding functon(within a zinc\nfinger domain) and phase separation functon(within IDR; PS mutation of Tyr to Ser in aa 101-\n210) to tightly bind onto chromatin targets. Interestingly, PS mutant failed to phase separate\nand also failed to interact with MLL1-T and had a weaker co-condensation with RNA POL II CTD.\nLastly, authors proposed to use heat shock protein to disrupt phase separation property of\nAKAP95; and on this line, they used a JD-PI95 fusion to treat MLLr AML. Preliminary data\nshowed the effects of JD-PI95 in vitro and in vivo. Overall, this work presented interesting\nfindings and studied a potentially important phenomenon related to phase separation, gene\nregulation and leukemia development. But some shown datasets were not carefully analyzed.\nWriting requires extensive editing. I have a few comments as listed below.\nMain comments.\n(1) This work used RNA-seq to define the differentially expressed genes after AKAP95 loss. But\nwhether these genes are upregulated or downregulated is not specified. This refers to Figure 3\nsuch as 3B and 3C. Authors seem to suggest downregulation in Fig 3C? The detected changes\nneed to be verified with other methods such as qPCR.\nRe: Thank you for the suggestion. We have added qPCR verification and carefully analyzed the\ndata in the revised manuscript. Due to the big variation of the mouse samples, we enclosed two\nbiological replicates in each group (WT or KO) for the heatmap showing the total differential\nexpress genes (Fig. 2H). Then, we separately analyzed molecular function of the upregulated (n\n= 377) and downregulated (n = 295) genes through GO analysis (Supplementary Fig. 4). We\nchose to check MLL-AF9 well-known targets and myeloid cell differentiation marker genes by\nqPCR, because these two categories are closely related to the observed phenotypes. All of\nthese genes were significantly changed in the three biological replicates (Fig. 2I).\n(2) What is the molecular basis underlying the AKAP95 IDR interaction with MLL1-T (and\nmaybe POL II CTD)?\nRe: In Fig. 3E, we showed that IDR1 of AKAP95 colocalized with MLL1T in Hela cells, but not\nother regions or phase separation-mutated IDR1. MLL1T is largely disordered and likely forms\ncondensate as shown in Fig. 6B (immunostaining with antibodies against the N terminal of\nMLL1). We speculate that AKAP95 IDR1 interacts with MLL1T IDRs, somewhat similar to\ntranscription activation domain (IDR) interacts with many co-activators IDR (Cruz et al., Mol\nCell, 2024, PMID: 39232584). As to why AKAP95 IDR1 co-condensed with MLL1T but not other\nregions, we compared the biochemical parameters of each fragment. IDR1 had similar fraction\nof negative or positive charged residues as MLL1T, and had negative net charge per residue,\nwhich matched with the positive outcome of MLL1T. We added this discussion in the revised\nmanuscript (Line 428-430).\nIt is also possible that the interaction of AKAP95 and MLL1T was through a third protein, for\nexample Pol II. Both proteins had been reported to bind to Pol II individually. Here, we think that\nfull dissection of the molecular detail about AKAP95 and MLL1T interaction is beyond the scope\nof this study.\n(3) In the Fig S9A rescue experiment, the PS mutant is expressed at the lower level than WT or\nZF mutation. This raises a concern. Also, authors only used THP1 cells in rescue. Other MLLr\ncell lines shall be used to confirm the findings. And authors shall use the cells in Fig S9A rescue\nexperiment for cell imaging of condensation of AKAP95 with MLLr and RNA POL II (like Figure\n4B).\nRe: Thank you for the suggestions. We did the following improvements in the revised\nmanuscript:\n1) we incorporated more technical repeats in THP1 rescue assay and optimized the WB result\n(Supplementary Fig. 11A).\n2) we added the data of Molm13 (another MLL-AF9 typed AML cell line) cell growth rescue (Fig.\n1F and Supplementary Fig. 11B).\n3) we did immunostaining against Pol II Ser2P (in Hela cells) and MLL1T (in THP1 cells) and\nobserved partial co-localization of AKAP95 with both proteins, but not the ZF- or PS-mutant\n(Fig. 5F and Fig. 6B).\n(4) The studies using JD-PI95 were incomplete. Peptide inhibitor is known to be hard to deliver\ninto cells or mice and probably is less stable. The concentrations of JD-PI95 used in Figure 6\nare not specified. A PI95 scramble control shall be used as an additional control for the JD-PI95\nfusion. What are the effects of JD-PI95 versus control on target gene expression or binding of\nAKAP95:MLLr at target genes?\nRe: We added more data to strengthen this part. 1) we measured the concentration of JD-PI95\nin THP1 cell (Supplementary Fig. 12H), about 19-38 nM, in the similar range of many small\nmolecular inhibitors. 2) we tested JD-PI95scr effects in different functional assays (cell\nfractionation, LacI-LacO puncta, double-luciferase assay, cell growth assay). In all these\nassays, JD-PI95scr showed inferior function compared to JD-PI95 (Fig. 6D-H). 3) we carried out\nPro-seq analysis of the peptide overexpressed THP1 cells. The on-going transcription of\nAKAP95 promoter-binding targets in JD-PI95 OE cells were significantly reduced compared to\nthe control cells. AKAP95 and MLL-AF9 joint targets RUNX2, SMC4 and NEK7 nascent RNA\nlevels were the lowest in JD-PI95 OE cells than in the control or JD-PI95scr OE cells\n(Supplementary Fig. 13C).\n(5) Grammar related issues and typos need to be addressed. There are many issues in the\nIntroduction and Discussion sections.\nRe: We have corrected these mistakes in the revised manuscript.\nMinor comments.\n(1) More datasets of MLLr versus non-MLLr human patient datasets shall be used to analyze\nAKAP95 expression.\nRe: In the revised manuscript Fig. 1, we included more datasets analysis, showing that AKAP95\nwas up-regulated in MLLr AML and MLLr B-ALL compared to each non-MLLr counterparts.\nAKAP95 expression was also higher in MLLr AML cells than the normal HSCs. qPCR analysis\nof AML patient samples showed that AKAP95 RNA levels were significantly higher in MLLr AML\npatients than in non-MLLr AML patients.\n(2) More MLLr cell lines such as MOLM13 shall be tested in Figure 1.\nRe: We have added Molm13 cell growth and rescue results in the revised manuscript (Fig. 1F\nand Supplementary Fig. 11B)\n(3) Are motifs shown in Figure 4D related to MLLr?\nRe: These conserved motifs are features of transcription factors NF-Y, Sp1, YY1 and Elk. All of\nthem are involved in regulation of stem cell fate determination and proliferation, including\nhematopoiesis. AKAP95 binding sites were enriched with these motifs, inferring it may\nprofoundly regulate gene expression in tumor cells in the similar way as NF-Y etc. transcription\nfactors in stem cells. We added this discussion in Line 220-222.\n(4) In Fig S9G, why did authors use MDA-MB-231 (a triple negative breast cancer cell line)?\nRe: We think the mechanism of AKAP95 regulating transcription in THP1 are two layers. The\nfirst mechanism is RNA synergize AKAP95 phase separation and recruiting Pol II CTD in the\nsame condensates. Through augmenting transcription machinery condensation, AKAP95\nenhances transcription. This mechanism is general in all types of cells. The second mechanism\nis AKAP95 partially co-localized with MLL1T and consequentially bound to the promoters of\nMLL-AF9 targets (enriched in AKAP95 ChIP binding sites) to regulate MLL-AF9 leukemia\nspecific gene expression. The latter mechanism is unique in MLLr leukemia cells, and explained\nwhy KD of AKAP95 only impairs MLLr leukemia cell growth but not other cells with different\ntypes of mutation.\nMDA-MB-231 cells were used in our previous study to check AKAP95 splicing function for cell\nproliferation. In the last version of manuscript, we originally planned to check whether the first\nlayer of mechanism itself is sufficient to support AKAP95 phase separation contributes to cell\nproliferation. In order to avoid the misunderstanding of the different research background, we\ndeleted MDA-MB-231 data in the revised manuscript. Instead, we added the two-layer\nmechanism of AKAP95 phase separation in regulating transcription in the discussion (Line 414-\n418, Line 430-432).\nReviewer #2 (Remarks to the Author): Expert in leukemia, PRO-seq, RNA-seq, and ChIP/CLIP-\nseq\nThe manuscript by Yan and colleagues studies the potential role of AKAP95 (aka AKAP8) in\ntranscriptional control. The investigators use a combination of genetics and genomics to make\nthe argument that AKAP95 is not only critical for MLL fusion protein action, but also for RNA\npolymerase functions through inducing condensate formation. The authors have generated a lot\nof data that indicates that AKAP95 is not required for normal cellular functions or for\nhematopoietic stem and progenitor cell function, even in the face of a bone marrow transplant.\nThese results suggest that AKAP95 is not required for the majority of transcriptional control,\neven under stress conditions when cells must rapidly cycle to replenish the bone marrow.\nNevertheless, when comparing cells with or without AKAP95, there were changes in about 5%\nof the transcripts, which likely describes the change in cell phenotype.\nThe challenge in trying to establish that an RNA binding protein is regulating transcription is\ndetermining whether the “chicken or the egg” comes first. That is, is RNA polymerase regulating\nAKAP95 condensate formation by making a nascent RNA that recruits AKAP95 to chromatin or\nis AKAP95 regulating transcription by binding to DNA or to RNA Polymerase? Unfortunately, the\ngenetic approaches employed are too slow to establish cause and effect relationships, as even the\nshRNAs take a couple of days to inhibit AKAP95. However, the investigators have a system\nin which they could integrate a degron tag into the endogenous alleles of AKAP95, which would\nallow rapid degradation of AKAP95. A short time course of degradation (0, 15’, 30’, 60’) coupled\nwith PRO-seq would define the changes in nascent transcription and determine if AKAP95 is\nrequired for transcription initiation and/or elongation. Without a doubt, this would be a lot of\nwork, but it is necessary to prove the conclusions that the authors are trying to make. Currently,\nthe work suggests that AKAP95 is not critical for RNA polymerase functions, but might\ncontribute to the fine tuning of some genes, perhaps even some that are important for MLL\nfusion protein action.\nRe: Thank you for the suggestion about the degron system. We found some doubts raised here\nare very similar as major comments, so we would like to answer them together as below.\nMajor Comments:\n1) The work relies heavily on shRNA knockdowns that trigger inflammation and have other off\ntarget effects. It would be useful to confirm the key findings using CRISPRs and to compare the\ndata with those in the DEPMAP.\nRe: We checked the DepMap dataset and found AKAP95 CRISPR score was negatively\ncorrelated to AKAP95 expression in AML cell lines. Most AKAP95 CRIPSR score is below zero,\nwhich suggests KD of AKAP95 would make a difference in cell proliferation. We added this data\nin the Supplementary Fig. 1D.\nWe always use scr shRNA as control, which should also trigger inflammation. Inflammation is\nthus not a concern. Moreover, crispr breaks DNA and can also cause DNA damage response\nand may also trigger inflammation and other off target effects.\n2) ChIP-seq data are not convincing as shown. The scales on the IGV screen shots are very\nsmall, which implies very low signal over the noise. This should be benchmarked to the signal of\nRNA Pol II to give the reader a comparison. It really looks like AKAP95 just binds nascent RNA,\nand it is getting crosslinked to DNA via its recruitment by RNA or through RNA polymerase.\nThat is, transcription is regulating AKAP95 rather than AKAP95 regulating transcription. This\ncould be tested by degrading RNA polymerase using a short treatment with -amanintin prior to\nChIP-seq analysis, which would establish that AKAP95 binds to the promoters identified. It\nreally looks like AKAP95 just binds nascent RNA, and it is getting crosslinked to DNA via its\nrecruitment by RNA or through RNA polymerase.\nRe: The small scales on IGV do not necessarily mean very low signal over the noise, as the\nnoise is better reflected on (1) the signals over the regions surrounding the (promoter) peaks\nand other genomic regions, and (2) the signals at the same (promoter) sites in the Ctrl (none KI)\nsample. Both signals are substantially lower than the signals at the promoter peaks in the KI\nsample, indicating the signal over noise ratio is high.\nFor comparison between AKAP95 ChIP peak and Pol II ChIP peak, we think this is not very\nmeaningful. Although Pol II ChIP peak at the certain promotors is much higher than AKAP95\nChIP peak, this may be caused by several reasons: (1) the endogenous AKAP95 is much lower\nthan Pol II (the transcripts of AKAP95 is significantly lower than that of POLR2A, see below\nfigure); (2) Pol II has much stronger affinity to promoter than AKAP95; (3) the antibodies against\nPol II is more sensitive than those against to Flag-mEGFP-AKAP95 (anti-flag).\nFig. R1. AKAP95 ChIP-seq signal was benchmarked to Pol II signal (A); AKAP95 mRNA level\nwas significantly lower than POLR2A (B).\nOur data suggest that AKAP95 does not independently bind to genomic DNA, but with the help\nof nascent RNA, Pol II and other DNA binding proteins (our previous IP-MS data). We do not\nagree that “transcription is regulating AKAP95 rather than AKAP95 regulating transcription”.\nRather, our data suggest a feed-forward model in which transcription promotes nascent RNA-\nmediated AKAP95 binding and phase separation as well as increased incorporation of other\ntranscription regulatory factors including MLL-fusion and Pol II, and these changes in turn\nenhance transcription.\nAs to your suggestion about using -amanintin to degrade Pol II before AKAP95 ChIP-seq, we\nthought this assay can distinguish whether interaction with Pol II mediates AKAP95 genome\nbinding. We had showed that inhibition of RNA transcription by actinomycin D reduced AKAP95\ngenome binding intensity (Supplementary Fig. 8B), phase separation mutation caused AKAP95\ndiffusive in nucleus and impaired binding to genomic DNA (Fig. 6B, Supplementary Fig. 11C).\n3) If one accepts the ChIP-seq data, then only 29 genes showed both differential regulation,\nChIP signal and CLIP signal, yet all RNA Pol II was affected by the expression of the mutants\n(Fig. 5E). It seems likely that this is just due to the cells growing more slowly (i.e., sick cells)\nrather than an interaction with chromatin.\nRe: If we only focus on the overlap of CLIP and ChIP binding genes (not include DEG in the\nanalysis), 1/4 of CLIP targets are ChIP targets, suggesting the possibility that nascent RNAs\nfunction as a platform for RBPs interacting with chromatin (Supplementary Fig. 7F). KD of\nAKAP95 caused 2372 genes downregulated, which were enriched in AKAP95 binding\npromoters/genes, suggesting AKAP95 positively regulates transcription (Fig. 4C).\n4) The genomic analysis in Figures 3-4 don’t hold together well. If AKAP95 is at 3348 promoters\n(roughly 1/3 of the expressed genes), why are so few genes affected by knockout of the gene?\nThe most common artifact of ChIP-Seq is a small signal at promoters, but if the signal is real,\nwhy is there no effect on H3K4me3 levels at MLL fusion protein targets (Fig. 3E)? Moreover,\nthere were large changes in H3K27ac genome wide (Fig. 3D), which implies that all genes were\nrepressed to some degree?\nRe: In the previous manuscript, Fig. 3 and Fig. 4 displayed different systems. H3K4me3 and\nH3K27Ac signals were measured in the pre-leukemia cells. Totally, 674 genes were\ndifferentially expressed (377 genes upregulated, 295 genes downregulated) between WT and\nAkap95-/- pre-leukemia cells. We double-checked the downregulation of MLL-AF9 targets by\nqPCR in the revised manuscript (Fig. 2I).\nH3K4me3 does not have to be affected if transcription changes.\nBy scanning through the whole chromosome, we did not see overall reduction of H3K27Ac. For\nsome genes, H3K27Ac signals were higher in KO cells than in WT cells (some IGV screenshots\nwere shown below). This is consistent with that some genes were upregulated, some genes\nwere downregulated in KO cells (Fig. 2H).\nFor Fig. 4, AKAP95 bound to 3348 promoters/genes in Hela cells. And 4270 genes altered\nexpression when AKAP95 was KD (2372 genes down-regulated, 1898 genes up-regulated),\nincluding both direct targets and indirect targets.\nFig. R2. IGV screenshot of H3K27Ac signal throughout the indicated chromosome.\n5) The PRO-seq data indicates no effect of AKAP95 on nascent transcription, but it is a very\nunusual plot in that there is as much antisense transcription as sense and there is little\ndivergence between the WT and the mutants. The histograms shown are also quite confusing in\nthat they show both sense and antisense transcription at -1000 bp from the TSS. The authors\nshould consider showing some screen shots that show a possible defect in nascent transcription\nmore clearly.\nRe: In the revised manuscript, we reanalyzed the Pro-seq data and found that the on-going\ntranscription rate of 414 AKAP95 targets (the common part of downregulated genes and\nAKAP95 binding promoters/genes) was highest in AKAP95-WT expressed cells, followed by ZF-\nmutant and then by PS-mutant expressed cells (Fig. 5E). Several representative genes IGV\nscreen shots were shown in Supplementary Fig. 9. As you can see, 1) the antisense\ntranscription reads were much less than the sense transcription, 2) gene transcripts in AKAP95-\nWT expressed cells showed much more reads than those in ZF- or PS-mutant expressed cells.\n6) If the fusion peptide truly inhibits condensate formation, then treating cells with the peptide\nand performing a short time course (0, 15’, 30’, 60’) of PRO-seq should define the role of\nAKAP95 in transcription control. It would be expected to cause a collapse of RNA polymerase at\nAKAP95-regulated loci.\nRe: In the revised manuscript, we carried out the Pro-seq analysis of nascent RNA profile in\npeptide treated THP1 cells. There was a huge difference on 3011 transcripts between JD-PI95\ntreated and non-treated cell, but the difference of metagene analysis between JD-PI95 and JD-\nPI95scr treated cells was not significant (Supplementary Fig. 13B). However, for certain MLL-\nAF9 targets, JD-PI95 treated samples displayed the lowest on-going transcription\n(Supplementary Fig. 13C). We think the time course experiments are challenging, as this could\nbe affected by other factors such as kinetics of peptide entry into cells.\nMinor:\n1) The authors might want to consider breaking the work into two manuscripts. The MLL story\ndoesn’t really integrate well with the HeLa and 293 cell work, as the is presumably not much\noverlap in regulated genes. There is a lot of data here, but it doesn’t fit together in a very\ncoherent manner.\nRe: In the revised manuscript, we did the following improvements to make the two parts\ncoherent:\n1) We provided more bioinformatic data, added fresh patient sample data, and reanalyzed the\nmouse MLL-AF9 leukemia data to strengthen AKAP95 relevance to MLLr leukemia (Fig. 1).\n2) We found MLL-AF9 targets (Olsen et al., Mol Cell, 2022, PMID: 35245435) were enriched in\nAKAP95 ChIP binding promoters/genes (although obtained from Hela cells). Moreover,\nAKAP95 ChIP binding intensity at MLL-AF9 targets were significantly higher than other\nbinding sites. The degree of down-regulation of AKAP95/MLL-AF9 joint targets was\nsignificantly greater than that of other AKAP95 targets when AKAP95 was loss, suggesting\nAKAP95 have a preference for regulating MLL-AF9 targets (Fig. 4C, 4D, 4E, 4F)\n3) We also check exogenous AKAP95 ChIP binding in THP1 cells and again found MLL-AF9\ntargets were enriched in the exogenous AKAP95 ChIP binding promoters/genes\n(Supplementary Fig. 11D, 11E, 11F). This echoes that AKAP95 and MLL1T had partial co-\nlocalization in THP1 cells (Fig. 6B).\n4) We provided the evidence that static and on-going transcription of several MLL-AF9 targets\nwere significantly reduced when AKAP95 phase separation targeting peptide JD-PI95 was\nadded into the culture of THP1 (Supplementary Fig. 13).\n2) The motif analysis doesn’t add anything to the story, as these are just binding sites\nassociated with promoters.\nRe：These binding motifs were conserved for transcription factors NF-Y, Sp1, YY1 and Elk,\nwhich are responsible for stem cell fate determination and proliferation. AKAP95 binding sites\nwere enriched with these binding motifs, inferring that AKAP95 may have profound impact on\ngene expression in tumor cells.\n3) It would probably be prudent to avoid calling myeloid progenitor cells LSCs unless formally\nproven to be LSC through limiting dilution analysis.\nRe: We have corrected this mistake in the revised manuscript.\nReviewer #3 (Remarks to the Author): Expert in MLL, MLL-AF9 model, and RBPs in\ntranscriptional regulation\nIn this study, Yan et al. investigate how the RNA binding protein AKAP95 contributes to MLL-\nrearranged (MLLr) leukemia through both transcriptional regulation and RNA splicing. This work\nis a followup on the authors’ previous manuscript published in Nature Cell Biology where they\nstudy AKAP95 condensate regulation and oncogenic function in breast cancer model. Here the\nresearchers found that AKAP95 is upregulated in MLLr leukemia compared to other types of\nacute myeloid leukemia and is essential for leukemia development but dispensable for normal\nblood cell formation. Mechanistically, AKAP95 uses both its RNA-binding ability and its capacity\nto undergo phase separation (form liquid-like droplets) to bind to chromatin and regulate gene\nexpression. The protein co-localizes with MLL fusion proteins and helps recruit RNA polymerase\nII to activate transcription. To target AKAP95 therapeutically, the researchers designed a\npeptide that disrupts its phase separation by recruiting the cell's protein quality control\nmachinery (HSP70). This peptide successfully reduced AKAP95's ability to regulate\ntranscription and impaired cancer cell growth, suggesting a potential new therapeutic strategy\nfor MLLr leukemia.\nAlthough there is a large set of work that will be of great interest there are some general\nconcerns about the internal logic of the study:\n1. Most of their mechanistic studies are performed in HELA cells or 293T cells and thus the\ndirect relevance in leukemia is not clearly defined.\nRe: In the revised manuscript, we did the following improvements to make the two parts\ncoherent:\n1) We provided more bioinformatic data, added fresh patient sample data, and reanalyzed the\nmouse MLL-AF9 leukemia data to strengthen AKAP95 relevance to MLLr leukemia (Fig. 1).\n2) We found MLL-AF9 targets (Olsen et al., Mol Cell, 2022, PMID: 35245435) were enriched in\nAKAP95 ChIP binding promoters/genes (although obtained from Hela cells). Moreover,\nAKAP95 ChIP binding intensity at MLL-AF9 targets were significantly higher than other\nbinding sites. The degree of down-regulation of AKAP95/MLL-AF9 joint targets was\nsignificantly greater than that of other AKAP95 targets when AKAP95 was loss, suggesting\nAKAP95 have a preference for regulating MLL-AF9 targets (Fig. 4C, 4D, 4E, 4F)\n3) We also check exogenous AKAP95 ChIP binding in THP1 cells and again found MLL-AF9\ntargets were enriched in the exogenous AKAP95 ChIP binding promoters/genes\n(Supplementary Fig. 11D, 11E, 11F). This echoes that AKAP95 and MLL1T had partial co-\nlocalization in THP1 cells (Fig. 6B).\n4) We provided the evidence that static and on-going transcription of several MLL-AF9 targets\nwere significantly reduced when AKAP95 phase separation targeting peptide JD-PI95 was\nadded into the culture of THP1 (Supplementary Fig. 13).\n2. It is unclear from the mechanistic studies why these are specifically MLL-dependent. Also, it\nis not clear that their mechanisms are directly related to MLL-associated targets. Importantly,\nonly 11 out of 128 MLL-AF9 targets are impacted and thus why are those targets special.\nMoreover, this does not make sense within the context of RNA polII transcriptional\nregulation.\nRe: We think the mechanisms for AKAP95 regulating transcription in THP1 are two layers. The\nfirst mechanism is RNA synergize AKAP95 phase separation and recruiting Pol II CTD in the\nsame condensates. Through augmenting transcription machinery condensation, AKAP95\nspeeds up transcription. This mechanism is general in all types of cells. The second mechanism\nis AKAP95 partially co-localized with MLL1T (Fig. 3C and Fig. 6B) and consequentially bound to\nthe promoters of MLL-AF9 targets (enriched in AKAP95 ChIP binding sites) to regulate MLL-\nAF9 leukemia specific gene expression. The promoters of some MLL-AF9 targets had higher\nAKAP95 ChIP binding intensities than other AKAP95 binding promoters. The degree of down-\nregulation of AKAP95/MLL-AF9 joint targets was significantly greater than that of other AKAP95\ntargets when AKAP95 was loss. All these together suggest that AKAP95 preferentially regulates\nsome MLL-AF9 targets (Fig. 4C, 4D, 4E, 4F). The latter mechanism is unique in MLLr leukemia\ncells, and explained why KD of AKAP95 only impairs MLLr leukemia cell proliferation but not\nother cells with different types of mutation.\n3. Is AKAP95 also show specificity for other leukemias driven by NPMc or NUP98? These\nleukemias are thought to be dysregulated transcriptionally similar to MLL fusions.\nRe: As the mechanism are two-layer, we are not sure if AKAP95 is also required for NPMc or\nNUP98 driven leukemias. Our preliminary data showed that exogenous AKAP95 and NUP98\nwere in the separate foci in 293T cells.\nFig. R3. Images of NUP98-mEGFP and AKAP95-mch overexpressed in 293T cells.\n4. Does the peptide delay leukemogenesis beside reduce disease burden?\nRe: We think it probably also delay leukemogenesis based on the effects on tumor cell growth in\nvitro 6G, but we have not performed time course for tumor growth in vivo so we don’t have data\nfor this.\n5. Does the peptide also have MLL specific requirement?\nRe: The peptide was designed to target AKAP95 phase separation. For its efficiency in inhibiting\ncancer cell proliferation, we still do not know how general the peptide can be applied for.\n6. Is this relevant to primary leukemia samples? Use of some primary AML patient material\nwould strengthen their findings. Depletion or use of the peptide in AML patients plus examining\ntheir targets in patient cohorts.\nRe: At present, we are not able to culture AML patient bone marrow cells. But we checked\npatient bone marrow mRNA from frozen tubes, and validated that AKAP95 were upregulated in\nMLLr patients compared to non-MLLr counterparts (Fig. 1D).\nSome additional, more specific points to be addressed are listed below:\nMajor points\na. Figure 1:\ni. Please provide protein evidence for differential AKAP5 expression across these cell lines. Is it\ncomparable to normal CD34+ cells?\nRe: WB analysis of several leukemia cell lines was shown in Supplementary Fig. 1B in the\nrevised manuscript. AKAP95 mRNA levels was significantly higher in MLLr leukemia cells than\nin normal HSC (Fig. 1C).\nii. 1C, its unclear what is being compared here.\nRe: Akap95 mRNA levels were compared in Fig. 1E in the revised manuscript.\niii. 1D Is reduced growth attributed to apoptosis? or increased differentiation?\nRe: Sorry, we did not take RNA-seq or apoptosis assay for those cell lines.\nb. Figure 2: there is a lack of transition between the experiments. Needs to be structured better.\ni. 2D: Morphological analyses should be supported by immunophenotypic evidence for myeloid\nmarkers.\nRe: We provided molecular evidence for the immunophenotype (CD11b and CD14 increase) in\nFig. 2I and Supplementary Fig. 5B.\nAnother study carried out by Iannis Aifantis group (Cell Stem Cell, PMID: 33450187) also\nshowed that KO of AKAP8 (AKAP95) caused CD11b and CD14 upregulation in the CRISPR\nscreening (see their Table 1S).\nii. Lines 138-139: where are these RFP positive cells being derived from? There are no RFP+\ncells introduced in this experiment so far.\nRe: We used different constructs for making lentiviral MLL-AF9 vectors. One is pMSCV-MLL-\nAF-IRES-GFP (a gift from Dr. Golam Mohi), the other one is pMIR-FLAG-MLL-AF9 (Addgene\n#71444). This information was described in the method section.\niii. Line 140: unclear which plating is being referred to here: related to Figure 2d and 2e or\nSupplemental figure 2C.\nRe: Fig. 2D was started with total MLL-AF9 transduced pre-leukemia cells, Fig. 2E is\nquantitative analysis of Fig. 2D. Supplementary Fig. 2C used sorted RFP+ pre-leukemia cells.\nFor Line 140, the colonies grown out in the third plating referred to cells transformed by pMSCV-\nMLL-IRES-GFP originated from Fig. 2D. We clarified this in the figure legend of Supplementary\nFig. 2C in the revise manuscript.\niv. Figures 2F-2G: please provide a guide that these experiments are related to secondary Tx of\nLGMP derived from primary recipients.\nRe: We added a guide in Fig. 2A and Fig. 2F.\nc. Figure 3:\ni. Panel A: unless specific DEG are being highlighted in the heat map its not informative. Please\nlabel the colorkey. What is the threshold?\nRe: Figure 3A have been modified as Fig. 2H in the revised manuscript. Due to the animal\nsamples big variation, we included two biological replicates for heatmap analysis, but validated\nsome important genes (MLL-AF9 targets and myeloid differentiation marker genes) in triplicates.\nThe cutoff for DEG in heatmap was |log FC| > 0.58.\n2\nii. Line 162-163: dysregulated is vague, could suggest up-or-downregulated. And which group?\nRe: We separately analyzed the up- and down-regulated genes in Supplementary Fig. 4.\niii. Panel B: Indicate if these are GO processes for DEG up or down in WT MA9.\nRe: We deleted this panel in the revised manuscript.\niv. Lines 165-166 and panels D and E. Authors initially show global enrichment plots for\nH3K27Ac and switch over to H3K4Ac in the trackplots in panel E. Although both are associated\nwith active transcription, they each denote specific properties. Additionally, they claim\ndifferences in H3K4me3, but the trackplots do not support this claim? Were there any\ndifferences in the enrichment for H3K27ac on the MLL-AF9 targets?\nRe: H3K4Ac was an error-labeling. We have corrected it in the revised manuscript. The\ndifference in H3K4me3 between samples was small. We have checked the H3K27Ac and\nH3K4me3 status for MLL-AF9 targets in Supplementary Fig. 5B.\nd. Figure 4 and related Supplemental Figure 5\ni. Given the poor image resolution in panels S5D and 4B, the foci and colocalization are not\nclear.\nRe: We had tried our best to take these images on advanced Zeiss LSM980 under the Airyscan\nmodule. The endogenous protein AKAP95 expression was quite low. Similar results were\nshown for other endogenous protein forming nuclear foci, such as UTX, MED1.\nii. Line 181 provide reference for “AKAP95 interacts with MLL-fusions”\nRe: We have modified the sentence.\niii. The authors endeavor to provide a mechanistic understanding of AKAP5 by performing\nCHIP-seq and CLIP-seq to suggest DNA and RNA-binding properties. Although informative, its\nunclear if these mechanisms play a role in regulating MLL-AF9 targets, specifically, their\nnascent transcription and/ or mRNA stability.\nRe: AKAP95 binding promoters/genes were enriched with MLL-AF9 targets (n = 56). AKAP95\nbinding intensity was higher on the MLL-AF targets than other genes (Fig. 4C, 4D). Moreover,\nthe degree of down-regulation of AKAP95/MLL-AF9 joint targets was significantly greater than\nthat of other AKAP95 targets when AKAP95 was loss (Fig. 4F). Representative MLL-AF9\ntargets ChIP, CLIP and RNA status was displayed in Fig. 4G and Supplementary Fig. 13C.\nOur data thus suggest that while AKAP95 regulates expression of many genes in the genome,\nsome of the MLL-fusion targets are particuarly dependent on AKAP95, at least in part because\ninteraction of MLLT and AKAP95. More details about the underlying mechanism could be found\nin the Response to the above Question 2.\ne. Figure 5 and related supplemental Figures 7 and 8\na. Please indicate in the text what “P1” stands for.\nRe: We have added this information in the revised manuscript (Line 255).\nb. Panels D: Label which enrichment plots are being shown here?\nRe: We have added the information in the revised Fig. 5D.\nc. Panel F: Is there an overlap between the Pro-seq occupancy with the MLL-AF9 target genes\nidentified in Figure 3?\nRe: The on-going transcription status of MLL-AF9 targets (NEK7, RUNX2, SMC4) were\ndisplayed in Supplementary Fig. 9 and Supplementary Fig. 13C.\nd. Panels 8E and 8D: is not in order with the text.\nRe: We have corrected it in the revised manuscript.\ne. Panel 8D: poor image resolution\nRe: Because the purified mch-CTD contained mch, the mch background was very high. But the\ndifference between AKAP95 WT and ZF-mutant at the presence or absence of RNA was still\nvisual obviously.\nf. Figure 6I: Please label what the barplots indicate.\nRe: The barplots showed luciferin intensity sum, indicating the tumor burden.\nMinor points\na. Inconsistent formatting across figure legends (e.g., some use full sentences while others use\nfragments)\nb. Some panels aren't fully explained (especially in supplementary figures)\nc. Statistical information could be more consistently presented.\nd. Scale bars are sometimes mentioned in text but not clearly visible in figures.\ne. Some abbreviations are used before being defined.\nf. Panel labels (A, B, C, etc.) aren't always clearly linked to their descriptions.\ng. Figure 1 legend, which could be clearer about the experimental setup and controls.\nh. Figure 5 legend, which has complex descriptions of multiple experiments that could be better\nstructured.\nRe: We have corrected many these errors in the revised manuscript.\nReviewer #4 (Remarks to the Author): Expert in RBPs in transcriptional regulation, ChIP-seq,\nRNA-seq, and CLIP-seq\nIn this manuscript, Yan et al. report that the co-condensation of AKAP95 and MLLr within the\nnucleus is essential for MLLr leukemogenesis. Mechanistically, they found that AKAP95\nactivates transcription by interacting with nascent RNAs on chromatin and recruiting Pol II\nthrough phase separation. Disrupting the co-condensation between AKAP95 and MLLr with\npeptides can inhibit tumor growth. These findings are intriguing and potentially important for\ntherapeutic applications; however, the following concerns need to be addressed to meet the\npublication criteria:\nThe writing is poor and requires thorough polishing. For example, the title does not adequately\ncapture the full scope of the manuscript. The abstract and many other sections also need further\nmodification.\nRe: We have edited and improved the writing in the revised manuscript.\nFor the upregulations or downregulations mentioned in the manuscript, it would be beneficial to\nprovide the fold-change values. For instance, in Figure 1C, the upregulated fold appears to be\nsubtle.\nRe: In the revised manuscript, Fig. 1E left panel showed the normalized counts from RNA-seq\ndata (GSE3725), the right panel displayed the fold change of AKAP95 mRNA levels by qPCR.\nIn Figure 1D, the authors should perform a rescue experiment to determine whether the\nobserved cell proliferation effects are direct or the result of off-target or secondary effects.\nRe: We had done rescue assay in Fig. 6A in the previous manuscript.\nIn Figure 3E, it seems that the H3K4me3 ChIP signal does not change in the two snapshots. If\nthere are changes, the authors need to quantify them.\nRe: The H3K4me3 ChIP signal difference was subtle. But the H3K27ac difference was very\nobvious. We marked the difference for specific genes in Supplementary Fig. 5B.\nFor Figure 4B, the figure quality is poor and contradicts their claims. The phase separation of\nAKAP95 and MLL1T is not visible, as no puncta or foci can be observed.\nRe: AKAP95 signal was from endogenous protein, MLL1T signal was from exogenous protein.\nThere were partial colocalization between AKAP95 and MLL1T puncta in Fig. 3C in the revised\nmanuscript. Similar result can be found in Fig. 6B, exogenous AKAP95 partially colocalized with\nendogenous MLL1N.\nIf AKAP95 regulates transcription by binding to nascent RNA, the authors should explain why\nthe ChIP targets and CLIP targets show minimal overlap (29 out of 556). Additionally, the CLIP\nis mislabeled as RIP in Figure 4F.\nRe: We reanalyzed the ChIP and CLIP data in the revised manuscript. Actually, a quarter of\nCLIP targets (n = 429) were ChIP targets (Supplementary Fig. 7F).\nResponse to reviewer’s comments\nWe have revised our manuscript following the format requirements of Nature\nCommunications. We also answered the reviewer’s questions and modified the\ntext accordingly.\nReviewer #1 (Remarks to the Author):\nThe authors have adequately addressed the previous comments through\nrevision and the inclusion of new data. Publication of this paper is therefore\nrecommended.\n++++++++++++++\nI have also been asked by the handling editor to provide my assessment to\nthe degree to which the authors have responded to the comments from\nReviewer #2, who was unavailable for this round of peer review. Here is my\nfeedback:\nIn general, the authors have addressed the concerns of Reviewer #2. It is of\nmy view that this study presents lots of quality data (reviewer 2 mentioned\nthis as well) and that this revised manuscript would be ready for publication\nafter the below minor revisions.\nThe reviewer 2 raised several main critiques and authors have clarified them\nwith either new results or additional analyses/explanations of existing\ndatasets. I would suggest authors to do the below minor edits and revisions:\n1/ Due to a general lack of effect seen with the new Pro-seq (as authors\nmentioned in the response letter), please remove the new data of\nSupplemental Fig 13B, which is just a single figure panel. Supplemental Fig\n13A can be merged with Supplemental Fig 12.\n(Btw: In the response to Reviewer 2’s concern 6, I can’t locate Supplemental\nFig 13C. It might be a typo of authors).\nRe: We apologize that we provided an incomplete Supplemental Fig. 13 in the\nlast submission. We have added the correct version in the revised manuscript.\nWe also double-checked the text to make sure all the information is\nadequately displayed.\nPro-seq analysis of JD-PI95 OE THP1 cells showed that there was a huge difference\non 916 transcripts between JD-PI95 treated and non-treated cell (Supplementary Fig.\n13b). Although the difference of metagene analysis between JD-PI95 and JD-PI95scr\ntreated cells was not significant, certain MLL-AF9 targets (RUNX2, SMC4 and NEK7)\ndisplayed the lowest on-going transcription in JD-PI95 treated cells (Supplementary\nFig. 13c).\n2/ In the Discussion, authors can add a new section of “Limitation of The\nStudy”, which is to include the further discussions and alternative\nexplanations based on the comments of all reviewers including the Reviewer\n2. The above edits would make a better paper without affecting overall\nquality.\nRe: We added a paragraph of “Limitation of the study” at the end of the\nmanuscript.\nLimitation of the study\nWe firstly showed that a substantial number of AKAP95 regulated genes in\nHela cells were MLL-AF9 targets. Then, in the rescue assay with MLLr cell line\nTHP1, we showed that both RNA-binding and phase separation properties\nwere important for AKAP95 regulating transcription fueled by MLL-AF9\noncogenic protein. In both systems, the degree of down-regulation of\nAKAP95/MLL-AF9 joint targets was more than that of other AKAP95 targets\nwhen AKAP95 was depleted, suggesting AKAP95 have a preference for\nregulating MLL-AF9 targets. Although our designed peptide JD-PI95,\nbridging AKAP95 and HSP70 to block AKAP95 engaged transcriptional condensates\nformation, is powerful to inhibit MLLr leukemia cell line proliferation in vitro\nand in vivo, its suppressive effect still needs to be test on clinical patient\nsamples.\n++++++++++++++\nReviewer #3 (Remarks to the Author):\nThe authors have mostly responded to the concerns and strengthened their\nclaims.\nReviewer #4 (Remarks to the Author):\nThe authors have done an excellent job revising the manuscript. All of my\nprevious concerns have been comprehensively resolved."}]

Decision letter