Engineered MED12 mutations drive uterine fibroid-like transcriptional and metabolic programs by altering the 3D genome compartmentalization

Uterine fibroid (UF) tumors originate from a mutated smooth muscle cell (SMC). Nearly 70% of these tumors are driven by hotspot recurrent somatic mutations in the MED12 gene; however, there are no tractable genetic models to study the biology of UF tumors because, under culture conditions, the non-mutant fibroblasts outgrow the mutant SMC cells, resulting in the conversion of the population to WT phenotype. The lack of faithful cellular models hampered our ability to delineate the molecular pathways downstream of MED12 mutations and identify therapeutics that may selectively target the mutant cells. To overcome this challenge, we employed CRISPR knock-in with a sensitive PCR-based screening strategy to precisely engineer cells with mutant MED12 Gly44, which constitutes 50% of MED12 exon two mutations. Critically, the engineered myometrial SMC cells recapitulate several UF-like cellular, transcriptional and metabolic alterations, including enhanced proliferation rates in 3D spheres and altered Tryptophan/kynurenine metabolism. Our transcriptomic analysis supported by DNA synthesis tracking reveals that MED12 mutant cells, like UF tumors, have heightened expression of DNA repair genes but reduced DNA synthesis rates. Consequently, these cells accumulate significantly higher rates of DNA damage and are selectively more sensitive to common DNA-damaging chemotherapy, indicating mutation-specific and therapeutically relevant vulnerabilities. Our high-resolution 3D chromatin interaction analysis demonstrates that the engineered MED12 mutations drive aberrant genomic activity due to a genome-wide chromatin compartmentalization switch. These findings indicate that the engineered cellular model faithfully models key features of UF tumors and provides a novel platform for the broader scientific community to characterize genomics of recurrent MED12 mutations and discover potential therapeutic targets.


Introduction
Uterine broids (UF), also called leiomyomas, are benign monoclonal neoplasms of the myometrium that represent the most common gynecologic tumors among reproductive-age women 1,2 . By the age of 50, more than 70% of all women (70% white and > 80% black) develop at least one broid tumor. UF are nonmalignant and not symptomatic in the majority of cases; however, in 15-30% of cases, they disrupt normal uterine functions, resulting in a wide range of severe health problems, including excessive uterine bleeding, anemia, defective implantation of an embryo, recurrent pregnancy loss, preterm labor and obstruction of labor and may mimic or mask malignant tumors in 15 to 30% of reproductive-age women 2 . Few medical treatments are available for UF, and many women opt to undergo a surgical hysterectomy.
However, such procedures create signi cant emotional stress on individual patients and a substantial nancial burden on society. These practices are estimated to cost $5.9 -$34.4 billion in the USA alone 3 .
At the genomic level, UF tumors have a relatively low mutational burden with few recurrent genetic mutations. Signi cantly, nearly 70% of UF tumors harbor somatic mutations in the MED12 gene, encoding the Mediator Complex Subunit 12 (MED12) 4 . Furthermore, translocation in the high mobility group AThook 2 (HMGA2) gene, recurrent loss of fumarate hydratase (FH), and deletion of collagen COL4A5-cells faithfully model several molecular features of UF biology. Signi cantly, our transcriptional and 3D genome mapping and analysis show that MED12 Gly4 mutations lead to genome-wide 3D chromatin organization and genome compartmentalization.

Results
Engineering MED12 Gly44 mutation in clonal myometrium smooth muscle cells: Notably, more than 50% of all MED12 exon two mutations are in the 44th codon and mutate Glycine into at least six other aa, indicating the signi cance of Glycine at this position for proper MED12 function. We set out to use CRISPR to knock in a respective mutation containing a DNA template in exon 2 of the MED12 gene in immortalized myometrial SMC line that retains the expression of various markers of primary SMC 23 . We utilized a CRISPR-based knock-in and qPCR-based single-cell colony selection strategy 24 (Fig. 1a, Supporting Fig. 1 ) to introduce Gly-44◊Asn mutation in exon 2 of MED12 and select single-cell colonies. The knock-in template is designed to also disrupt the PAM sequence while altering the aa at the 44th codon. We transiently delivered WT Cas9, sgRNA, and a custom-designed knock-in single-stranded DNA (ssDNA) oligo template through nucleofection. We then single-cell-sorted, grew individual nucleofected cells and performed qPCR-based colony screening on genomic DNA from > 400 single-cell colonies ( Supplementary Fig. 2), we obtained multiple clonal cell lines that are homozygous and heterozygous for Gly-44 mutations (Fig. 1b-c). We validated the WT and mutant allele frequency using CRISPR-TIDER analysis ( Supplementary Fig. 3). Critically, since MED12 is on the X chromosome, one allele undergoes random epigenetic inactivation. Thus, we performed additional screening from the cDNA of the single-cell clones to identify several clonal cell lines expressing the mutant Gly-44 MED12 in the mRNA as validated by cDNA sequencing (Fig. 1c). Western blot analysis shows that the Gly44 mutation does not alter MED12 protein stability (Fig. 1d).
MED12 Gly44 mutation recapitulates UF-speci c proliferation defects. A formidable challenge in establishing an in vitro model of broid tumors has been the rapid disappearance of cells carrying MED12 mutations when the broid tumor cells are cultured in vitro 21,22 . This is believed to be due to a reduced proliferative capacity in 2D culture conditions in vitro. To test whether such a slower proliferation defect can cause the disappearance of mutant cells from the population, we initially analyzed the mixed population of cells right after the CRISPR knock-in. Our targeted sequencing and CRISPR-TIDER analysis indicated that the mixed population contained ~ 36% WT allele, 7% knock-in allele (Gly 44 mutant), and 57% indel alleles (likely MED12 KO) after initial CRISPR editing. We then continuously cultured this mixed population and performed targeted sequencing at exon 2 of MED12 at the 4th, 6th, 7 th, and 9th weeks after the initial gene editing. Signi cantly, we observed that the mixed population reached ~ 100% WT allele while gradually losing both the G44 mutant and the indel alleles (Fig. 1e), supporting the observed phenotype of MED12 mutant primary SMC cells 21,22 . To quantify the proliferation defects in these cells more precisely, we studied clonally expanded pure populations (from single cells) of MED12 WT, Gly44 mutant, or KO SMC cells. We used Incucyte live cell imaging platform to robustly detect cell proliferation defects by monitoring individual nuclei counts over several days. Critically, the Gly44 mutant cells are less proliferative than WT cells but better than the KO cells (Fig. 1f). The time course experiment indicates that the WT cells double in ~ 23 hrs, whereas the MED12 Gly44-mutant cells double every ~ 32 hrs in 2D adherent conditions. Although interesting, these ndings raised the question of how such a mutation drives UF tumorigenesis if it leads to reduced cell proliferation. We, therefore, tested whether the reduced proliferation is due to the restrictive 2D culture conditions. The MED12 Gly44 mutation increased cell-autonomous and non-autonomous proliferation capacity.
MED12 Gly 44 mutations are causal in inducing higher cell proliferation and, eventually, tumor formation in humans and mice. To understand whether the reduced proliferation phenotype is an artifact of 2D culture conditions, we cultured the WT and the engineered mutant cells in 3D spheroid conditions. Notably, the MED12 mutants formed signi cantly larger spheroids than WT cells (Fig. 1g-h), indicating the signi cance of culture conditions in studying MED12 mutations. On average, we observed that MED12 mutant spheres grew 2-4 times larger than the WT colonies. At the same time, the KO cells did form any spheres (not shown), indicating that the engineered MED12 Gly44 mutation is UF-relevant and is a gain-of-function mutation.
Notably, the MED12 mutant UF is composed of mutant SMC and non-mutant tumor-associated broblasts and stromal cells at nearly equal rates 20 , suggesting that the mutant cells cause the proliferation of non-mutant cells in a cell non-autonomous fashion. To test whether the engineered mutant cells will also increase the proliferation in non-mutant cells, we performed co-cultured experiments with uorescently labeled (mCherry) non-mutant cells. We quanti ed the rate of proliferation in uorescently labeled non-mutant cells. In line with the data in Fig. 1g, we observed larger volume spheroids when mutant cells were cultured with non-mutant cells. We dissociated the spheroids to reveal whether the larger spheroid formation is partly due to the increased proliferation of non-mutant cells. We counted the number of mCherry(+) cells from each condition. This analysis indicated that mutant cells enhance the proliferation capacity of the non-mutant cells in the microenvironment ( Supplementary  Fig. 4).
The engineered MED12 Gly44 mutation alters the global metabolism in smooth muscle cells. The altered proliferation rates are driven by overall cellular metabolic and transcriptional reprogramming. Uterine broid tumors have distinct metabolic and bioenergetic needs. For example, uterine broid tumors are known to be depleted of Tryptophan but replete with Kynurenine, a product of Tryptophan metabolism 25 (Fig. 2a), indicating the signi cant metabolic differences between these two cells. Speci cally, MED12 mutation leads to the downregulation of 14 metabolites while upregulating, a larger number, of 21 metabolites (Fig. 2b-c).
Critically, increased 5-HIAA, Kynurenine, thiamine, N-carbomyl-L-aspartate, and reduced Tryptophan, mevalonic acid, N-acetylaspartic acid, glyceraldehyde were the top differentially regulated metabolites. Tryptophan is an essential amino acid that the body needs to acquire from the diet and is metabolized into Kynurenine. Our detailed quanti cations show that while Tryptophan is signi cantly (p < 0.01, t-test) depleted in MED12 mutant cells, Kynurenine levels are abnormally elevated (p < 0.01, t-test) (Fig. 2d). In line with this, Tryptophan metabolism was the top enriched metabolic term when all differentially regulated metabolites were analyzed together (Fig. 2e). Notably, our group previously reported that the reduced Tryptophan levels in MED12 mutant uterine broids are driven by increased levels and activity of an enzyme called Tryptophan 2,3-Dioxygenase-2 (TDO2) that converts Tryptophan into Kynurenine 26 . We, therefore, tested whether our engineered cells have elevated levels of TDO2 protein. Critically, the western blot analysis shows that the mutant cells have markedly increased levels of TDO2, whose levels are not detectable in WT and the MED12 KO cells (Fig. 2f). These ndings highlight that the engineered Gly44 mutation recapitulates known metabolic reprogramming in primary UF tumors 25 mutations and minimal clonal heterogeneity compared to WT clones. Differential expression analysis showed that MED12 mutation drives the differential expression of ~ 2000 genes, consistent in both MED12 mutant clones (987 upregulated and 1137 downregulated, p-adj < 0.05) (Fig. 3a). Most critically, the MED12 Gly44 mutations resulted in differential expression of a distinct set of genes compared to MED12 knock-out cells ( Supplementary Fig. 5), supporting the overall hypothesis that the UF-associated MED12 mutations are not loss of function, but a gain of function mutations.
The aberrant transcriptional program of MED12 Gly44 mutant cells is reminiscent of broid tumors. To assess whether these differentially expressed genes are comparable and relevant to broid tumors, we analyzed them with the recent gene expression program of normal myometrium (n = 15) and MED12 mutation harboring broid tumors (n = 15) reported by Moyo et al. We detected ~ 5500 differentially expressed genes (P-adj < 0.01) between normal myometrium and UF samples (Fig. 3b). Notably, the gene set enrichment analysis (GSEA) highlighted that several hallmarks are shared among the mutant cells and primary broid tumors. For example, hallmarks of cell cycle-related genes, MYC and E2F target genes, and DNA repair genes are substantially upregulated in the mutant cells as well as primary UFs. On the other hand, protein secretion and heme metabolism genes are among the most downregulated genes. (Fig. 3c). In line with GSEA, the gene ontology (GO) analyses on differentially expressed genes in Gly44 mutant cells and broid tumors identi ed a common set of biological processes between these two samples. For example, the upregulated genes in Gly44-mutant and broid tumors are enriched for cell cycle and DNA replication-related gene ontology (GO) terms ( Supplementary Fig. 6). Conversely, the downregulated genes in our MED12 mutant cells and primary broids included a group of cell adhesion and extracellular matrix (ECM) reorganization genes, indicating that, Gly44 mutation also recapitulates the abnormal ECM feature of human UFs 27,28 .
We next assessed the epigenome of these cells to see whether MED12 mutation leads to aberrant gene expression changes through the altered epigenome. Since MED12 is a critical regulator that mediates promoter-enhancer interaction, we acquired a genome-wide map of Histone H3 Lysine 27 (H3K27ac) histone modi cation which marks active enhancers and promoters 29,30 by Cut & Tag 31 . Notably, differential peak analysis identi ed that 4904 peaks gained the H3K27ac mark, while 482 of the regulatory elements nearly lost all H3K27ac signal (Fig. 3e), indicating that MED12 Gly44 mutation results in increased genomic activity at most regulatory elements. To identify whether this change in H2K27ac chromatin state had a corresponding change in target gene expression, we analyzed the expression change in their target genes mapped by their genomic proximity to the H3K27ac peak (< 10kb). Notably, the targets of gained peaks in MED12 mutant cells had a signi cantly higher expression in these cells compared to WT cells (Fig. 3f). Conversely, the gene targets of lost peaks in MED12 mutants dramatically reduced their expression in these cells (Fig. 3g). These ndings indicated that MED12 mutations induced gene expression changes is, in part, due to reprogrammed epigenome, at least of the H3K27ac chromatin states.
MED12 mutations lead to enhanced expression of collagen genes in 3D culture conditions. Fibroid tumors are known to have aberrant remodeling of extracellular matrix and signi cantly higher production of collagen 20,27,32 . Recent transcriptome and epigenome pro ling by Moyo et al. 33 , also highlighted signi cantly higher expression of collagen genes in broid tumors. Surprisingly, we did not nd higher expression of collagen genes in our 2D cultured cells. We, therefore, wondered whether this is due to culture conditions. We thus obtained RNA-seq expression pro les of these cells cultured in 3D sphere conditions. Signi cantly, we found that culture conditions (2D vs. 3D) had a dramatic impact on gene expression programs. Indeed, > 80% of all gene expression variations could be explained by culture conditions whereas MED12 mutations induced gene expression alterations contributed to 12% of variations (Fig. 3h). More importantly, under 3D culture conditions, we observed signi cantly higher expression of collagen and ECM genes in both WT and mutant cells. However, mutant cells had signi cantly higher expression (Fig. 3i). Of the 45 collagen genes, 20 of them were expressed at higher levels in 3D conditions, and 15 collagen genes had signi cantly higher expression in MED12 mutant cells (Fig. 3i) as exempli ed in the RNA-Seq tracks for COL5A3 gene loci (Fig. 3j). Furthermore, global gene expression program under 3D conditions had a higher resemblance to the primary broid gene programs.
For example, in 2D conditions, we found 166 upregulated and 181 downregulated genes common between MED12 mutant cells vs broid tumors. However, these numbers increased to 539 and 569 genes, respectively when cells were cultured in 3D conditions ( Supplementary Fig. 7). These ndings highlight that the impact of MED12 mutations is further enhanced in 3D conditions and the engineered mutations recapitulate induced collagen gene expression, speci cally in 3D conditions. The MED12 Gly44 mutation alters DNA synthesis and renders cells sensitive to DNA-damaging agents.
The above data and cell proliferation rates suggested that MED12 G44 mutation leads to abnormal cell cycle, DNA replication, and repair. We, therefore, tested whether MED12 mutant cells have aberrant cell cycles by analyzing the 5-ethynyl-2′-deoxyuridine (EdU) incorporation and DNA content levels. Notably, the MED12 mutant cells have a signi cantly higher percentage of cells in the S-phase (p < 0.035), indicating an abnormal rate of DNA synthesis and progression of the DNA replication fork (Fig. 4a, Supplementary  Fig. 8). These ndings support a recent report that MED12 mutant UF samples have increased replication stress due to abnormal progression of the replication fork and increased R-loop formation 34 . Notably, if unresolved, abnormal progression or stalling of replication may lead to structural genomic alterations or excessive DNA damage through replication fork collapse 35,36 . In line with this, the MED12 mutant UF contains the highest number of structural variations in the genome 37,38 ; indeed, more than 60% of MED12 mutant UFs have large-scale structural genomic aberrations 39,40 .
The above ndings led us to test whether the mutant cells have increased DNA damage at the basal level and are differentially sensitive to DNA-damaging agents such as Carboplatin. To this end, we measured γ-H2AX as a proxy for DNA damage/repair activity. Notably, in line with recent ndings 34 , we did not see a signi cant increase in total γ-H2AX at the basal level by western blot (Fig. 4b). However, the immuno uorescence staining shows a detectable difference between overall gH2AX signal intensity, indicating a potential DNA damage/repair activity difference between these two cells (Fig. 4c). Interestingly, we saw signi cantly more DNA damage accumulation in MED12 mutant cells in response to Carboplatin in both MED12 mutant cell lines both by western blot and IF (Fig. 4c, Supplementary Fig. 9). The MED12 mutant Fibroid tumors are known to have higher abnormal progression of the replication fork and increased R-loop formation 34 . We, therefore, tested whether primary broid tumors also have higher DNA damage/repair activity compared to normal myometrium. We performed an immunohistochemistry analysis of gH2AX on a well-annotated tissue microarray containing normal myometrium and MED12 mutant broid tumors (n = 10). To quantify levels if γ-H2AX in a robust and unbiased way, we trained a machine learning algorithm to assess γ-H2AX levels at a single cell level (methods). Critically, we nd that MED12 mutant broid tumors have detectable and substantially higher overall γ-H2AX levels, indicating higher DNA damage and repair activity compared to normal myometrium ( Fig. 4d-e, Supplementary  Fig. 10). Notably, the γ-H2AX levels within the same broid tumors across smooth muscle cells vs. the stromal cells were comparable (Fig. 4f).
The above ndings led us to investigate whether the MED12 mutant cells, that display higher activity of DNA repair gene, potentially due to a basal level DNA damage, would be selectively more vulnerable to additional DNA damage. We, therefore, performed long-term live-cell imaging to assess relative apoptosis rates (Caspase 3/7 staining, Biotum) over four days. We observed signi cant apoptotic cell death selectively in MED12 mutant cells compared to WT cells (Fig. 4g), indicating a potential therapeutically exploitable vulnerability in these mutant cells.
The MED12 Gly44 mutations alter genome-wide 3D chromatin organization and genome compartmentalization. The mediator complex is a critical player in genome organization that links distal regulatory elements to gene promoters 7,8,33,41 . We, therefore, studied whether the abnormal transcriptional program downstream of MED12 mutations is due to altered 3D genome organization. Depending on the scales of organization, the nuclear genome can be categorized into at least three distinct layers in 3D space 42,43 . Globally, the chromosomal DNA is organized into two distinct compartments: A or B. The A compartment is generally associated with gene transcription and active histone modi cation marks such as H3K27ac and H3K4m3, while the B compartment is mostly composed of heterochromatin. At a ner scale, (usually ~ hundreds of Kb in size), the mammalian genome is organized as topologically associated domains (TAD), whose boundary can prevent the erroneous interactions between the enhancer and wrong target genes. At the nest scale, when a Hi-C library is sequenced deep enough, the chromatin loops that reveals high-resolution promoter-enhancer interactions can be identi ed. Each layer of genome organization has been linked with proper gene regulation and human diseases [42][43][44][45] . To study how MED12 Gly 44 mutation alters the 3D genome organization, we employed high-resolution Hi-C technology and obtained 804,255,654 chromatin contact pairs in WT and 717,644,659 contact pairs in MED12 mutant cells ( Supplementary Fig. 11a).
We observed a striking difference on Hi-C maps between WT and Mutant cells. Compared with WT cells, the MED12 mutant cell Hi-C map showed much more pronounced plaided or checkboard patterns ( Fig. 5a), suggesting the global change in interactions involved with A/B compartment. We observed signi cant changes in the compartment state annotations between the two cell types, as exempli ed by the eigenvectors track above the Hi-C maps (Fig. 5a). Globally, we found that 7.04% of B compartments switched to A compartment, while 9.45% of B compartments switched to A compartment (Fig. 5b).
Integrating gene expression data with 3D genome organization shows that these changes in genomic compartments alters gene expression activity. More speci cally, the genes within the compartments that switched from inactive B compartments to active A compartments were signi cantly upregulated, whereas the genes in the A-to-B switching regions were downregulated (Fig. 5c). For example, the ABCB5 gene, which was in B compartment and silenced in WT cells, was in a B-to-A compartment region and highly expressed in MED12 mutant cells (Fig. 5d) In addition to the compartmentalization switch, we also observed enhanced 3D chromatin interactions between the compartments of the same types but reduced inter-compartment interactions. As demonstrated in global average contact frequencies across all compartments in the genome (Fig. 5e), MED12 mutant cells have signi cantly higher intra-compartments (A-to-A or B-to-B) interaction frequencies (Fig. 5f). Interestingly, the global compartment strength is primarily driven by enhanced A-to-A interactions and reduced A-to-B interactions, as B-to-B compartment interactions are comparable in WT and mutant cells (Fig. 5f). Finally, we predicted 23,487 chromatin loops in WT cells and a comparable number of 23,261 loops in MED12 mutant cells, using a machine-learning software that we recently developed 46 . Of these, ~ 20,000 loops were common, and ~ 3000 were cell-type speci c chromatin loops ( Supplementary Fig. 11b-c). These ndings indicate that the differential gene expression changes downstream of MED12 mutation are partly due to altered 3D genome organization.

Discussion
Recurrent somatic MED12 mutations drive broid tumors in 70% of cases. Unfortunately, the MED12 mutant cells from these lesions could not be isolated and maintained in culture conditions 47,48 . This formidable challenge limited the ability to create a tractable genetic model system to deeply characterize metabolomics and genomics of pure populations of MED12 mutant cells. In this study, we utilized CRISPR genome engineering to introduce broid-relevant recurrent MED12 mutation at the endogenous MED12 locus. We generated multiple pure populations of MED12 mutant cells that recapitulate in vitro features of UF broid tumors.
Notably, more than 50% of all recurrent MED12 exon two mutations are mutating the Glycine aa at the 44th codon into at least six other aa, indicating that altering Gly at this position results in signi cant structural and functional alterations in MED12. Interestingly, Gly is the smallest and the only aa that contains Hydrogen as its side chain, whereas all other amino acids contain Carbon 49 . As such, Gly may have a critical impact on both structure and function of the protein because the sidechain-less form of Glycine provides conformational exibility and can also bind to phosphate, e.g., ATP, in the case of kinase pockets 49 . Our ndings also support the clinical 4,50,51 and mouse genetic 40 data that the recurrent MED12 Gly 44 mutations are gain of function and "oncogene" in UF tumorigenesis 19 . However, the exact mechanism of how these genetic alterations drive UF pathogenesis is poorly understood.  1,20,40 . Notably, we identify a potential therapeutically exploitable vulnerability in the mutant cells as these cells are signi cantly more sensitive to a chemotherapeutic agent, Carboplatin. Our detailed metabolomics and transcriptomics analysis show that the engineered MED12 mutation results in robust metabolic and gene expression changes that are highly reminiscent of primary broid tissues. Therefore, the model system we present here may be a valuable asset for the larger research community to study and target UF-relevant MED12 mutations.
Importantly, in addition to being mutated in > 70% of UF 4 , MED12 exon two mutations are also observed in breast broadenomas and phyllodes tumors(59%) 52,53 , uterine leiomyosarcomas (7-30%) 54 , chronic lymphocytic leukemias (5%) 55 , and colorectal cancers (0.5%) 54 . Therefore, whether the mutant MED12 in these diseases also results in similarly altered 3D chromatin compartmentalization is yet to be understood. To this end, the genome-engineered strategy we present here could be explored to introduce similar mutations in other cellular models and comparatively study the outcomes to assess whether the same MED12 mutations result in similar aberrant transcriptomic and 3D genome organization changes.
Our study has some limitations. Firstly, we engineered one of the several MED12 mutations in exon 2.
Whether other recurrent hot spot mutations result in the same phenotype is yet to be determined.

Declarations
Data availability: All metabolomics and gene expression data will be made publicly available.
Con ict of Interest: The authors have no relevant nancial or non-nancial interests to disclose
Single-cell colony qPCR scanning and validation: Single-cell colonies were split into replicate plates after the colonies grew. One of the replicate plates was washed with PBS twice, Tris-HCL(ph 8.5) was added, and the cells were scraped off with pipette tips. Then, cells were transferred to qPCR plates (#4306737, Applied biosystem). Cells were incubated at 95 °C /15 min for lysis, then cooled on ice for 1 min. Then, they were treated with Proteinase K (55 °C /30 min) (# EO0492, Thermo) and incubated at 95 °C /10 min for proteinase inactivation. After this, they were transferred to new qPCR plates, and the same amount of lysis was used per reaction (reactions were performed as duplicates). qPCR was performed using Fast SYBR™ Green Master Mix (4385616, Thermo Fisher) and the same reverse primer (AGGTCATGAAGGCAAACTCAG), with two different forward primers WT/Mut (GCCTTGAATGTAAAACAAGGTTTC/ GCCTTGAACGTGAAGCAGAACTTC) to detect positive colonies.
After detecting mutation-positive colonies, the gDNA was extracted from the replicate plates using the Purelink genomic DNA mini kit (#K182002, Thermo), and RNA was extracted using the Zymo research Quick RNA miniprep kit(#R1054). Isolated RNA was converted to cDNA (#4387406, Applied biosystem).
The MED12-exon2 region was ampli ed using primers F/R (GAAGAGTGATGTTTGAGGGCG/ AGGTCATGAAGGCAAACTCAG) from gDNA using primers F/R (CTTCGGGATCTTGAGCTACG/ CAGCCAAGTCAGTGAACCAA) from the cDNA, then sent for sanger sequencing for mutation validation.
CRISPR TIDER analysis: After sorting for double positive (mCherry+GFP) cells, half of the cells were seeded as a population separately from single-cell colonies. These cells were then used to detect population-level CRISPR knock-in rate using CRISPR-TIDER 57 analysis. They were subsequently passaged over 9 weeks to determine if MED12 mutation abundance changed in the population over time. Also, mutant positive colonies were analyzed using CRISPR-TIDER to differentiate homozygous/heterozygous mutation. For TIDER, three PCR amplicons were produced following the website's protocol ( http://shinyapps.datacurators.nl/tider/ ). Control and sample PCR amplicons were produced using F/R (GAAGAGTGATGTTTGAGGGCG/ AGGTCATGAAGGCAAACTCAG) primers on genomic DNA. Reference PCR amplicons were produced using two overlapping primers (ACTGACGGCCTTGAACGTGAAGCAGAACTTCAATAACCAGCC/ AGGCTGGTTATTGAAGTTCTGCTTCACGTTCAAGGCCGTACG) and the same set of F/R primers for the control and sample PCRs described by the website's protocol. Then, sanger sequencing results (ACGT / NU core) (.ab1 les) were uploaded using the default settings on the website.  Figure 6). DESeq2 normalized exon counts were used in GSEA (v4.0.2) 63 analysis in default settings.
All leiomyoma and myometrium RNA-seq data were downloaded from the NCBI-GEO data repository via accession GSE128242 and original publication data processing steps were followed 33 . Heatmaps of differentially expressed genes were plotted in R (cran.r-project.org) using pheatmaps (Kolde, Raivo / v.1.0.12, 2019).
Incucyte live cell imaging: Incucyte Live cell imaging system (Sartorius) was used for tracking cell proliferation. The system took a photo of cell plates every two hours in different image channels (Phase/Green or Red). For cell nucleus counting, 1 µM SiR-DNA nuclear dye was used (Cytoskeleton, #SC007) and captured using the red channel. At the end of the experiment, proliferation data were analyzed using the Incucyte analysis tool and p-values were calculated using the incucyte raw data.
Relative proliferation was normalized to the starting time.
EdU staining: Cells (4X10^5) were seeded in six-well plates one day before Edu staining. Then, cells were treated with 10 uM Edu for 90 minutes following the manufacturer's protocol (Click-iT™ Plus EdU Alexa Fluor™ 488 Flow Cytometry Assay Kit, Thermo,# C10632). Next, cells were stained for DNA content using FxCycle™ Violet Stain (Thermo, # F10347)( 1 µl violet for 1 ml media). Lastly, cells were analyzed using ow cytometry, and the results were analyzed using FlowJo.
H3K27Ac cut & tag and analysis: Benchtop CUT&Tag 31 V.2 protocol was slightly modi ed to pro le genome-wide H3K27ac. Brie y, Concanavalin A-coated (ConA) beads (10 µl/sample) were washed using binding buffer (100 µl/sample) twice and kept on ice until the cells were ready. Cells were then harvested and counted to obtain 100,000 cells for each sample. Then, cells were centrifuged and washed one-time using wash buffer. After washing, cells were centrifuged and resuspended in wash buffer (100 µl/sample). Next, ConA beads were added to each sample while vortexing gently. The bead-sample mixture was rotated for 10 minutes at RT. Next, samples were put on a magnet stand to clear the liquid. Following this, samples were resuspended in ice-cold antibody buffer (50 µl/reaction) while vortexing and then kept on ice. Afterward, 3 µl H3K27ac antibody (ab4729, Abcam) was added to each sample while vortexing gently. Samples were incubated overnight at 4 °C on a nutator. The next day, samples were cleared using a magnet stand. Secondary antibody (ABIN101961) mixture (2 µl antibody diluted in 100 µl dig-wash buffer for each sample) was added to each sample while vortexing. After 1 hour of incubation at RT on a nutator, samples were cleared and washed twice using Dig-wash buffer (1 ml/sample). Then, the pA-Tn5 adapter complex (2.5 µl pA-Tn5 in 47.5 µl Dig-300 buffer) was added to each sample while vortexing and samples were incubated for 1.5 hours at RT on a nutator. Here, we used pAG-Tn5 from EpiCypher (Cat No: 15-1117). After the incubation, samples were cleared and washed twice using Dig-300 buffer (1 ml/sample). Next, 300 µl tagmentatiton buffer was added to each sample, and they were incubated for 1.5 hours at 37 °C. To stop tagmentatiton, 10 µl 0.5M EDTA, 3 µl 10% SDS, and 2.5 µl 20 mg/ml Proteinase K was added to each sample. After adding Proteinase K, samples were vortexed immediately and incubated overnight at 37 °C. The following day, samples were incubated at 50 °C for 30 minutes. To isolate DNA, 300 µl phenol-chloroform was added to samples and mixed by vortexing. Each mixture was transferred into a phase-lock tube (129046, Qiagen) and centrifuged at 16,000 g for 3 minutes at RT. Next, 300 µl chloroform was added to each sample and inverted 10 times to mix. Samples were then centrifuged at 16,000 g for 3 minutes at RT. After centrifugation, the aqueous layer was transferred to new tubes containing 750 µl 100% ethanol and mixed well with pipetting. Samples were incubated on ice for 5 minutes and centrifuged for 15 minutes at 4 °C 16,000 g. The liquid was removed (pellet may not be visible), and 1 mL 100% ethanol was added to rinse the pellet. Then, samples were centrifuged for 1 minute at 4 °C 16,000 g. The liquid was carefully removed, and samples were air-dried for about 15 minutes. Next, the pellet was dissolved using 25 µl TE buffer (10 mM Tris-HCl pH 8, 1 mM EDTA supplemented with 1:400 diluted RNAse A). To remove potential RNA contaminants, samples were then incubated 10 minutes at 37 °C. Library preparation was performed as described in Benchtop CUT&Tag V.2 protocol. The library was sequenced using NextSeq 500 (2 x 75 bp) to obtain 5 million reads per sample.
Apoptosis assay: Cells were seeded into 96 well plates at a density of 1.5 X 10 3 cells/well. The following day, treatments were performed using 65 uM/75um Carboplatin (IC30/IC40 concentration, (Selleckchem,# S1215) mixed with 1:1000 diluted Caspase 3/7 dye (10403, Biotum). Then, cells were monitored using the Incucyte live cell imaging system using phase and green channels. The apoptosis rate was determined using the green integrated intensity/con uency values, and the results were plotted using the Incucyte cell imaging analysis.
Immuno uorescence staining: Approximately 1.5x10 cells were seeded onto coverslips in 6-well plates. The next day, cells were treated with the indicated concentrations of Carboplatin for three days. Then, cells were washed with PBS and xed using 4% paraformaldehyde in PBS for 10 minutes at RT. After xation, cells were washed three times with ice-cold PBS and incubated with 0.25% Triton X-100 in PBS for permeabilization. Next, cells were washed three times for 5 minutes with PBS and blocked using 1% BSA, 22.52 g/mL glycine in PBS-T (PBS+0.1 Tween 20) for 1 hour at RT. After blocking, cells were incubated with primary antibodies (Phospho-Histone H2A.X (Ser139)(1:1000)( Cell Signaling,#2577)) prepared with 1% BSA in PBS-T overnight at 4 °C in a humidi ed chamber. The next day, cells were washed three times for 5 minutes with PBS-T, and then they were incubated with a secondary antibody (Alexa Fluor 594, Invitrogen #A-11012) prepared in 1% BSA in PBS-T for 1 hour at RT. Afterward, cells were washed three times for 5 minutes using PBS-T. Next, coverslips were mounted onto microscopy slides using a mounting medium with DAPI (S36939, Thermo Fisher ). Finally, slides were visualized using the EVOS cell imaging system, and the images were analyzed using ImageJ software. Relative γH2AX levels were drawn and the p-value (Two-sided unpaired t-test ) was calculated in Prism-GraphPad (9.4.1).
Liquid chromatography-mass spectrometry (LC-MS) and analysis: Cells were seeded on 10 cm plates and the medium was completely aspirated once they reached ~70-80 % con uence. Then, cells were rinsed with ice-cold PBS twice and add 1 ml 80% (vol/vol) methanol (cooled -80 °C). Then, cells were scraped on ice with a cell scraper and collected lysate in a conical tube. The lysate was incubated at -80 °C for 5 min and vortexed at room temperature for 1 min. Repeat that step two times. Then, the lysate was incubated at -80 °C overnight for protein precipitation. The next day, they were centrifuged at 20000xg for the pellet was fully dissolved in 8M urea buffer, and protein concentrations were determined using a BCA assay (Thermo, #23225). The same amount of metabolomes based on protein amount were submitted for LC-MS. The metabolome was analyzed in the NU metabolomics core facility. Then, all metabolome peak areas of samples were normalized to their TIC (Total ion count). And, normalized peak area per metabolite results were analyzed on Metaboanalyst 5.0 67 (https://www.metaboanalyst.ca/).
High-throughput chromosome conformation capture (Hi-C) and data processing: The Hi-C was performed using the Arima-HiC Kit (A510008, Arima Genomics) as instructed by the manufacturer. Approximate 1 million WT/Mut cells were harvested, counted, and xed with 1% formaldehyde and quenched with 0.125 M glycine at room temperature. The xed cells were digested with the restriction enzyme and end-labelled with Biotin-14-dATP, followed by proximity ligation. Then reverse-crosslinking was performed to the ligated samples and sheared into 300-500bp fragments. The Biotin-labeled DNA fragments were then end-repaired following adapter ligation and PCR ampli cation. Hi-C libraries were generated using KAPA Library Quanti cation Kit (KAPA Biosystems) and quality-checked according to the manufacturer's protocol.
The mapping, ltering, and binning of the data were done using the runHiC(v0.8.6) pipeline. First, the adapters of the Hi-C FASTQ les were trimmed using Trim Galore(v0.4.5), and then runHiC aligned the trimmed FASTQ les to the hg38 human reference genome with Burrows-Wheeler Aligner. Then, lowquality reads and PCR duplicates were removed. Read pairs were then used to couple aligned reads, and redundant PCR artifacts and read pairs aligned to the same restriction fragments were ltered out before the next stage. The binning stage binned the reads at 5-kb, 10-kb, 50-kb, 1-Mb, 10-Mb, and 50-Mb resolution and performed the ICE normalization at the same time. After the binning state, ICE normalized matrices .mcool les were generated for downstream analyses.
High-throughput chromosome conformation capture (Hi-C) Compartment Analysis: The compartment analysis for WT/Mut HiC was performed using cooltools. The A/B compartments PC1 values at 100-kb resolution were called using cooltools eigs-cis command. The scatter plot of PC1 values before and after the MED12 Gly44 mutation was plotted using the ggplot2 package of R (v4. For the co-culture spheroid experiment, the same number of HUtSMC (ATCC, #PCS-460-011) and mCherry positive hTERT cells (WT / Mut / KO) were seeded together in Corning ultra-low attachment plates (1500/1500 cells per well). After four days, spheroid photos were taken using the EVOS cell imaging system and spheroid volumes were calculated using ImageJ. Then, spheroids were collected and the cells were dispersed using trypsin-EDTA (0.25%) (Gibco,# 25200056). Then, the mCherry positive cell rate in the population was calculated using ow cytometry.
High-resolution analysis of   bp A to B compartment switch regions after the MED12 mutation. c. The boxplots show the log2 fold change of gene expression (MED12 mutant vs. WT cells) for the genes located within B to A switch, stable, and A to B switch region. The center line represents the median, the box contains the interquartile range, and the whiskers extend to the 5 th and 95 th percentiles. The statistical test was performed using a two-sided Wilcoxon test (ns, not signi cant; ***p-value < 0.001, ****p-value < 0.0001).) d. A regional example displaying the gene ABCB5 is located in the B to A switch region after the MED12 mutation, along with regional H3K27ac binding enrichment and expression fold change increase. e. Saddle plot displays the genome-wide compartment interaction in wild-type (Left) and MED12 Mut (Right) cells based on Hi-C compartment eigenvectors. f. The boxplots show the quanti cation of the compartment strength, A to A, B to B, and A to B interaction strength in WT and Mut cells. The center line represents the median, the box contains the interquartile range, and the whiskers extend to the 5 th and the 95 th percentiles. The statistical test was performed using a two-sided Wilcoxon test (ns, not signi cant; ***p-value < 0.001, ****p-value < 0.0001).)

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