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 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 phenocopies the YAP-induced cell proliferation, migration, and invasion phenotypes and correlates with poor patient survival. Mechanistically, we identify FSTL-1 as a major direct client of TRAM2 that is involved in these phenotypes. Thus, TRAM2 is a key novel mediator of YAP-induced oncogenic proliferation and cellular invasiveness.

CONCLUSIONS

YAP is a transcription co-factor that binds to thousands of enhancer loci and stimulates tumor aggressiveness. Using unbiased functional approaches, we dissect YAP enhancer network and characterize TRAM2 as a novel mediator of cellular proliferation, migration, and invasion. Our findings elucidate how YAP induces cancer aggressiveness and may assist diagnosis of cancer metastasis.

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.

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.

Analysis of numerous RNA-seq datasets reveals a recurrent sample-specific length bias that causes frequent false positive calls by gene-set enrichment analyses, leading to functional misinterpretation of the data. Its removal requires methods that allow the integration of gene length as sample-specific covariate.

Functional CRISPR screen identifies AP1-associated enhancer regulating FOXF1 to modulate oncogene-induced senescence

BACKGROUND

Functional characterization of non-coding elements in the human genome is a major genomic challenge and the maturation of genome-editing technologies is revolutionizing our ability to achieve this task. Oncogene-induced senescence, a cellular state of irreversible proliferation arrest that is enforced following excessive oncogenic activity, is a major barrier against cancer transformation; therefore, bypassing oncogene-induced senescence is a critical step in tumorigenesis. Here, we aim at further identification of enhancer elements that are required for the establishment of this state.

RESULTS

We first apply genome-wide profiling of enhancer-RNAs (eRNAs) to systematically identify enhancers that are activated upon oncogenic stress. DNA motif analysis of these enhancers indicates AP-1 as a major regulator of the transcriptional program induced by oncogene-induced senescence. We thus constructed a CRISPR-Cas9 sgRNA library designed to target senescence-induced enhancers that are putatively regulated by AP-1 and used it in a functional screen. We identify a critical enhancer that we name EnhAP1-OIS1 and validate that mutating the AP-1 binding site within this element results in oncogene-induced senescence bypass. Furthermore, we identify FOXF1 as the gene regulated by this enhancer and demonstrate that FOXF1 mediates EnhAP1-OIS1 effect on the senescence phenotype.

CONCLUSIONS

Our study elucidates a novel cascade mediated by AP-1 and FOXF1 that regulates oncogene-induced senescence and further demonstrates the power of CRISPR-based functional genomic screens in deciphering the function of non-coding regulatory elements in the genome.