Epigenetic regulators represent a promising new class of therapeutic targets for cancer. Enhancer of zeste homolog 2 (EZH2), a subunit of Polycomb repressive complex 2 (PRC2), silences gene expression via its histone methyltransferase activity. Here we report that the oncogenic function of EZH2 in castration-resistant prostate cancer (CRPC) is independent of its role as a transcriptional repressor. Instead, it involves the ability of EZH2 to act as a co-activator for critical transcription factors including the androgen receptor (AR). This functional switch is dependent on phosphorylation of EZH2, and requires an intact methyltransferase domain. Hence, targeting the non-PRC2 function of EZH2 may have significant therapeutic efficacy for treating metastatic, hormone-refractory prostate cancer.

If trait-associated variants alter regulatory regions, then they should fall within chromatin marks in relevant cell types. However, it is unclear which of the many marks are most useful in defining cell types associated with disease and fine mapping variants. We hypothesized that informative marks are phenotypically cell type specific; that is, SNPs associated with the same trait likely overlap marks in the same cell type. We examined 15 chromatin marks and found that those highlighting active gene regulation were phenotypically cell type specific. Trimethylation of histone H3 at lysine 4 (H3K4me3) was the most phenotypically cell type specific (P < 1 × 10−6), driven by colocalization of variants and marks rather than gene proximity (P < 0.001). H3K4me3 peaks overlapped with 37 SNPs for plasma low-density lipoprotein concentration in the liver (P < 7 × 10−5), 31 SNPs for rheumatoid arthritis within CD4+ regulatory T cells (P = 1 × 10−4), 67 SNPs for type 2 diabetes in pancreatic islet cells (P = 0.003) and the liver (P = 0.003), and 14 SNPs for neuropsychiatric disease in neuronal tissues (P = 0.007). We show how cell type–specific H3K4me3 peaks can inform the fine mapping of associated SNPs to identify causal variation.

High-throughput CRISPR screens have shown great promise in functional genomics. We present MAGeCK-VISPR, a comprehensive quality control (QC), analysis, and visualization workflow for CRISPR screens. MAGeCK-VISPR defines a set of QC measures to assess the quality of an experiment, and includes a maximum-likelihood algorithm to call essential genes simultaneously under multiple conditions. The algorithm uses a generalized linear model to deconvolute different effects, and employs expectation-maximization to iteratively estimate sgRNA knockout efficiency and gene essentiality. MAGeCK-VISPR also includes VISPR, a framework for the interactive visualization and exploration of QC and analysis results. MAGeCK-VISPR is freely available at http://bitbucket.org/liulab/mageck-vispr.Electronic supplementary materialThe online version of this article (doi:10.1186/s13059-015-0843-6) contains supplementary material, which is available to authorized users.