A CRISPR-Cas9 screen identifies essential CTCF anchor sites for estrogen receptor-driven breast cancer cell proliferation

Estrogen receptor α (ERα) is an enhancer activating transcription factor, a key driver of breast cancer and a main target for cancer therapy. ERα-mediated gene regulation requires proper chromatin-conformation to facilitate interactions between ERα-bound enhancers and their target promoters. A major determinant of chromatin structure is the CCCTC-binding factor (CTCF), that dimerizes and together with cohesin stabilizes chromatin loops and forms the boundaries of topologically associated domains. However, whether CTCF-binding elements (CBEs) are essential for ERα-driven cell proliferation is unknown. To address this question in a global manner, we implemented a CRISPR-based functional genetic screen targeting CBEs located in the vicinity of ERα-bound enhancers. We identified four functional CBEs and demonstrated the role of one of them in inducing chromatin conformation changes in favor of activation of PREX1, a key ERα target gene in breast cancer. Indeed, high PREX1 expression is a bona-fide marker of ERα-dependency in cell lines, and is associated with good outcome after anti-hormonal treatment. Altogether, our data show that distinct CTCF-mediated chromatin structures are required for ERα- driven breast cancer cell proliferation

CUEDC1 is a primary target of ERα essential for the growth of breast cancer cells

Breast cancer is the most prevalent type of malignancy in women with ∼1.7 million new cases diagnosed annually, of which the majority express ERα (ESR1), a ligand-dependent transcription factor. Genome-wide chromatin binding maps suggest that ERα may control the expression of thousands of genes, posing a great challenge in identifying functional targets. Recently, we developed a CRISPR-Cas9 functional genetic screening approach to identify enhancers required for ERα-positive breast cancer cell proliferation. We validated several candidates, including CUTE, a putative ERα-responsive enhancer located in the first intron of CUEDC1 (CUE-domain containing protein). Here, we show that CUTE controls CUEDC1 expression, and that this interaction is essential for ERα-mediated cell proliferation. Moreover, ectopic expression of CUEDC1, but not a CUE-domain mutant, rescues the defects in CUTE activity. Finally, CUEDC1 expression correlates positively with ERα in breast cancer. Thus, CUEDC1 is a functional target gene of ERα and is required for breast cancer cell proliferation

A comprehensive enhancer screen identifies TRAM2 as a key and novel mediator of YAP oncogenesis

Background: Frequent activation of the co-transcriptional factor YAP is observed in a large number of solid tumors. Activated YAP associates with enhancer loci via TEAD4-DNA-binding protein and stimulates cancer aggressiveness. Although thousands of YAP/TEAD4 binding-sites are annotated, their functional importance is unknown. Here, we aim at further identification of enhancer elements that are required for YAP functions. Results: We first apply genome-wide ChIP profiling of YAP to systematically identify enhancers that are bound by YAP/TEAD4. Next, we implement a genetic approach to uncover functions of YAP/TEAD4-associated enhancers, demonstrate its robustness, and use it to reveal a network of enhancers required for YAP-mediated proliferation. We focus on EnhancerTRAM2, as its target gene TRAM2 shows the strongest expression-correlation with YAP activity in nearly all tumor types. Interestingly, TRAM2 phenocopi

Recurrent functional misinterpretation of RNA-seq data caused by sample-specific gene length bias.

Data normalization is a critical step in RNA sequencing (RNA-seq) analysis, aiming to remove systematic effects from the data to ensure that technical biases have minimal impact on the results. Analyzing numerous RNA-seq datasets, we detected a prevalent sample-specific length effect that leads to a strong association between gene length and fold-change estimates between samples. This stochastic sample-specific effect is not corrected by common normalization methods, including reads per kilobase of transcript length per million reads (RPKM), Trimmed Mean of M values (TMM), relative log expression (RLE), and quantile and upper-quartile normalization. Importantly, we demonstrate that this bias causes recurrent false positive calls by gene-set enrichment analysis (GSEA) methods, thereby leading to frequent functional misinterpretation of the data. Gene sets characterized by markedly short genes (e.g., ribosomal protein genes) or long genes (e.g., extracellular matrix genes) are particularly prone to such false calls. This sample-specific length bias is effectively removed by the conditional quantile normalization (cqn) and EDASeq methods, which allow the integration of gene length as a sample-specific covariate. Consequently, using these normalization methods led to substantial reduction in GSEA false results while retaining true ones. In addition, we found that application of gene-set tests that take into account gene-gene correlations attenuates false positive rates caused by the length bias, but statistical power is reduced as well. Our results advocate the inspection and correction of sample-specific length biases as default steps in RNA-seq analysis pipelines and reiterate the need to account for intergene correlations when performing gene-set enrichment tests to lessen false interpretation of transcriptomic data

Some algebro-geometric aspects of the SL(2,R) Wess-Zumino-Witten model of strings on an AdS(3) background

The SL(2, R) WZW model of strings on an ADS3 background is investigated in the spirit of J.Maldacena's and H.Ooguri's approach (hep-th/0001053) and (hep-th/0005183). Choosing a standard, but most general three-variable parametrization of the SL(2, R) group element g, the system of equations for the Operator Product Expansion (OPE) relations is analysed. In the investigated SL(2, R) case, this system is consistent if each three points on the complex plane lie on a certain hypersurface in CP3. A system of three nonlinear first-order differential equations has been obtained for the parametrization functions. It was demonstrated also how the mathematical apparatus of generalized functions and integral geometry can be implemented in order to modify the integral operators, entering the Kac-Moody and Virasoro algebras

Long reads capture simultaneous enhancer-promoter methylation status for cell-type deconvolution.

MOTIVATION: While promoter methylation is associated with reinforcing fundamental tissue identities, the methylation status of distant enhancers was shown by genome-wide association studies to be a powerful determinant of cell-state and cancer. With recent availability of long reads that report on the methylation status of enhancer-promoter pairs on the same molecule, we hypothesized that probing these pairs on the single-molecule level may serve the basis for detection of rare cancerous transformations in a given cell population. We explore various analysis approaches for deconvolving cell-type mixtures based on their genome-wide enhancer-promoter methylation profiles. RESULTS: To evaluate our hypothesis we examine long-read optical methylome data for the GM12878 cell line and myoblast cell lines from two donors. We identified over 100 000 enhancer-promoter pairs that co-exist on at least 30 individual DNA molecules. We developed a detailed methodology for mixture deconvolution and applied it to estimate the proportional cell compositions in synthetic mixtures. Analysis of promoter methylation, as well as enhancer-promoter pairwise methylation, resulted in very accurate estimates. In addition, we show that pairwise methylation analysis can be generalized from deconvolving different cell types to subtle scenarios where one wishes to resolve different cell populations of the same cell-type. AVAILABILITY AND IMPLEMENTATION: The code used in this work to analyze single-molecule Bionano Genomics optical maps is available via the GitHub repository https://github.com/ebensteinLab/Single_molecule_methylation_in_EP

Long reads capture simultaneous enhancer-promoter methylation status for cell-type deconvolution.

MOTIVATION: While promoter methylation is associated with reinforcing fundamental tissue identities, the methylation status of distant enhancers was shown by genome-wide association studies to be a powerful determinant of cell-state and cancer. With recent availability of long reads that report on the methylation status of enhancer-promoter pairs on the same molecule, we hypothesized that probing these pairs on the single-molecule level may serve the basis for detection of rare cancerous transformations in a given cell population. We explore various analysis approaches for deconvolving cell-type mixtures based on their genome-wide enhancer-promoter methylation profiles. RESULTS: To evaluate our hypothesis we examine long-read optical methylome data for the GM12878 cell line and myoblast cell lines from two donors. We identified over 100 000 enhancer-promoter pairs that co-exist on at least 30 individual DNA molecules. We developed a detailed methodology for mixture deconvolution and applied it to estimate the proportional cell compositions in synthetic mixtures. Analysis of promoter methylation, as well as enhancer-promoter pairwise methylation, resulted in very accurate estimates. In addition, we show that pairwise methylation analysis can be generalized from deconvolving different cell types to subtle scenarios where one wishes to resolve different cell populations of the same cell-type. AVAILABILITY AND IMPLEMENTATION: The code used in this work to analyze single-molecule Bionano Genomics optical maps is available via the GitHub repository https://github.com/ebensteinLab/Single_molecule_methylation_in_EP

A CRISPR-Cas9 screen identifies essential CTCF anchor sites for estrogen receptor-driven breast cancer cell proliferation

Estrogen receptor α (ERα) is an enhancer activating transcription factor, a key driver of breast cancer and a main target for cancer therapy. ERα-mediated gene regulation requires proper chromatin-conformation to facilitate interactions between ERα-bound enhancers and their target promoters. A major determinant of chromatin structure is the CCCTC-binding factor (CTCF), that dimerizes and together with cohesin stabilizes chromatin loops and forms the boundaries of topologically associated domains. However, whether CTCF-binding elements (CBEs) are essential for ERα-driven cell proliferation is unknown. To address this question in a global manner, we implemented a CRISPR-based functional genetic screen targeting CBEs located in the vicinity of ERα-bound enhancers. We identified four functional CBEs and demonstrated the role of one of them in inducing chromatin conformation changes in favor of activation of PREX1, a key ERα target gene in breast cancer. Indeed, high PREX1 expression is a bona-fide marker of ERα-dependency in cell lines, and is associated with good outcome after anti-hormonal treatment. Altogether, our data show that distinct CTCF-mediated chromatin structures are required for ERα- driven breast cancer cell proliferation

A CRISPR-Cas9 screen identifies essential CTCF anchor sites for estrogen receptor-driven breast cancer cell proliferation

\u3cp\u3eEstrogen receptor α (ERα) is an enhancer activating transcription factor, a key driver of breast cancer and a main target for cancer therapy. ERα-mediated gene regulation requires proper chromatin-conformation to facilitate interactions between ERα-bound enhancers and their target promoters. A major determinant of chromatin structure is the CCCTC-binding factor (CTCF), that dimerizes and together with cohesin stabilizes chromatin loops and forms the boundaries of topologically associated domains. However, whether CTCF-binding elements (CBEs) are essential for ERα-driven cell proliferation is unknown. To address this question in a global manner, we implemented a CRISPR-based functional genetic screen targeting CBEs located in the vicinity of ERα-bound enhancers. We identified four functional CBEs and demonstrated the role of one of them in inducing chromatin conformation changes in favor of activation of PREX1, a key ERα target gene in breast cancer. Indeed, high PREX1 expression is a bona-fide marker of ERα-dependency in cell lines, and is associated with good outcome after anti-hormonal treatment. Altogether, our data show that distinct CTCF-mediated chromatin structures are required for ERα- driven breast cancer cell proliferation.\u3c/p\u3

A CRISPR-Cas9 screen identifies essential CTCF anchor sites for the mitogenic function of ER-alpha in breast cancer

Estrogen receptor α (ERα) is an enhancer activating transcriptional factor, a key driver of breast cancer, and a main target for cancer therapy. ER-mediated gene regulation requires proper chromatin-conformation to stimulate physical linkage between ER-bound enhancers and their target promoters. A major determinant of chromatin structure is CTCF that anchors chromatin domains. However, whether CTCF-binding elements (CBEs) are essential for ER mitogenic activity is unknown. To address this question in a global manner, we implemented a CRISPR-based functional genetic screening approach targeting CBEs located in the vicinity of ERα-bound enhancers. We identified four functional CBEs and demonstrated the role of one in inducing chromatin conformation changes in favor of activation of PREX1, a key ERα target gene in breast cancer. Indeed, high PREX1 expression predicted sensitivity to loss of ER, and good survival to anti-hormonal treatment. Altogether, our data show that CTCF-mediated chromatin structure is required for ER mitogenic function