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Model-based analysis of regulation of gene expression (MARGE) is a framework for interpreting the relationship between the H3K27ac chromatin environment and differentially expressed gene sets. The framework has three main functions: MARGE-potential, MARGE-express, and MARGE-cistrome. MARGE-potential defines a regulatory potential (RP) for each gene as the sum of H3K27ac ChIP-seq signals weighted by a function of genomic distance from the transcription start site. The MARGE framework includes a compendium of RPs derived from 365 human and 267 mouse H3K27ac ChIP-seq data sets. Relative RPs, scaled using this compendium, are superior to superenhancers in predicting BET (bromodomain and extraterminal domain) -inhibitor repressed genes. MARGE-express, which uses logistic regression to retrieve relevant H3K27ac profiles from the compendium to accurately model a query set of differentially expressed genes, was tested on 671 diverse gene sets from MSigDB. MARGE-cistrome adopts a novel semisupervised learning approach to identify cis-regulatory elements regulating a gene set. MARGE-cistrome exploits information from H3K27ac signal at DNase I hypersensitive sites identified from published human and mouse DNase-seq data. We tested the framework on newly generated RNA-seq and H3K27ac ChIP-seq profiles upon siRNA silencing of multiple transcriptional and epigenetic regulators in a prostate cancer cell line, LNCaP-abl. MARGE-cistrome can predict the binding sites of silenced transcription factors without matched H3K27ac ChIP-seq data. Even when the matching H3K27ac ChIP-seq profiles are available, MARGE leverages public H3K27ac profiles to enhance these data. This study demonstrates the advantage of integrating a large compendium of historical epigenetic data for genomic studies of transcriptional regulation., (© 2016 Wang et al.; Published by Cold Spring Harbor Laboratory Press.)

The CRISPR/Cas9 system has revolutionized mammalian somatic cell genetics. Genome-wide functional screens using CRISPR/Cas9-mediated knockout or dCas9 fusion-mediated inhibition/activation (CRISPRi/a) are powerful techniques for discovering phenotype-associated gene function. We systematically assessed the DNA sequence features that contribute to single guide RNA (sgRNA) efficiency in CRISPR-based screens. Leveraging the information from multiple designs, we derived a new sequence model for predicting sgRNA efficiency in CRISPR/Cas9 knockout experiments. Our model confirmed known features and suggested new features including a preference for cytosine at the cleavage site. The model was experimentally validated for sgRNA-mediated mutation rate and protein knockout efficiency. Tested on independent data sets, the model achieved significant results in both positive and negative selection conditions and outperformed existing models. We also found that the sequence preference for CRISPRi/a is substantially different from that for CRISPR/Cas9 knockout and propose a new model for predicting sgRNA efficiency in CRISPRi/a experiments. These results facilitate the genome-wide design of improved sgRNA for both knockout and CRISPRi/a studies., (© 2015 Xu et al.; Published by Cold Spring Harbor Laboratory Press.)

Transcription factor cistromes are highly cell-type specific. Chromatin accessibility, histone modifications, and nucleosome occupancy have all been found to play a role in defining these binding locations. Here, we show that hormone-induced DNase I hypersensitivity changes (ΔDHS) are highly predictive of androgen receptor (AR) and estrogen receptor 1 (ESR1) binding in prostate cancer and breast cancer cells, respectively. While chromatin structure prior to receptor binding and nucleosome occupancy after binding are strikingly different for ESR1 and AR, ΔDHS is highly predictive for both. AR binding is associated with changes in both local nucleosome occupancy and DNase I hypersensitivity. In contrast, while global ESR1 binding is unrelated to changes in nucleosome occupancy, DNase I hypersensitivity dynamics are also predictive of the ESR1 cistrome. These findings suggest that AR and ESR1 have distinct modes of interaction with chromatin and that DNase I hypersensitivity dynamics provides a general approach for predicting cell-type specific cistromes.

We present a powerful application of ultra high-throughput sequencing, SAGE-Seq, for the accurate quantification of normal and neoplastic mammary epithelial cell transcriptomes. We develop data analysis pipelines that allow the mapping of sense and antisense strands of mitochondrial and RefSeq genes, the normalization between libraries, and the identification of differentially expressed genes. We find that the diversity of cancer transcriptomes is significantly higher than that of normal cells. Our analysis indicates that transcript discovery plateaus at 10 million reads/sample, and suggests a minimum desired sequencing depth around five million reads. Comparison of SAGE-Seq and traditional SAGE on normal and cancerous breast tissues reveals higher sensitivity of SAGE-Seq to detect less-abundant genes, including those encoding for known breast cancer-related transcription factors and G protein-coupled receptors (GPCRs). SAGE-Seq is able to identify genes and pathways abnormally activated in breast cancer that traditional SAGE failed to call. SAGE-Seq is a powerful method for the identification of biomarkers and therapeutic targets in human disease.

Transcription factors play an important role in orchestrating the activation of specific networks of genes through targeting their proximal promoter and distal enhancer regions. However, it is unclear how the specificity of downstream responses is maintained by individual members of transcription-factor families and, in most cases, what their target repertoire is. We have used ChIP-chip analysis to identify the target genes of the ETS-domain transcription factor ELK1. Two distinct modes of ELK1 target gene selection are identified; the first involves redundant promoter binding with other ETS-domain family members; the second occurs through combinatorial binding with a second transcription factor SRF, which specifies a unique group of target genes. One of the most prominent groups of genes forming the ELK1 target network includes classes involved in core gene expression control, namely, components of the basal transcriptional machinery, the spliceosome and the ribosome. Amongst the set of genes encoding the basal transcription machinery components, are a functionally linked subset of GTFs and TAFs. Our study, therefore, reveals an unsuspected level of coordinate regulation of components of the core gene expression control machinery and also identifies two different modes of promoter targeting through binding with a second transcription factor or redundant binding with other ETS-domain family members.

Selective activity of a specific set of enhancers defines tissue-specific gene transcription. The pioneer factor FOXA1 has been shown to induce functional enhancer competency through chromatin openings. We have previously found that FOXA1 is recruited to thousands of regions across the genome of a given cell type. Here, we monitored the chromatin structure at FOXA1 binding sites on a chromosome-wide scale using formaldehyde assisted isolation of regulatory elements (FAIRE). Surprisingly, we find that a significant fraction of FOXA1-bound sites have a relatively closed chromatin conformation linked to a shift of the epigenetic signature toward repressive histone marks. Importantly, these sites are not correlated with gene expression in a given cell type suggesting that FOXA1 is required, but not sufficient, for the functional activity of bound enhancers. Interestingly, we find that a significant proportion of the inactive FOXA1-bound regulatory sites in one cell type are actually functional in another cellular context. We found that at least half of the FOXA1 binding sites from a given cell type are shared with another cell lineage. Mechanisms that restrict the activity of shared FOXA1-bound enhancers likely play a significant role in defining the cell-type-specific functions of FOXA1.

Pre-mRNA processing often occurs in coordination with transcription thereby coupling these two key regulatory events. As such, many proteins involved in mRNA processing associate with the transcriptional machinery and are in proximity to DNA. This proximity allows for the mapping of the genomic associations of RNA binding proteins by chromatin immunoprecipitation (ChIP) as a way of determining their sites of action on the encoded mRNA. Here, we used ChIP combined with high-density microarrays to localize on the human genome three functionally distinct RNA binding proteins: the splicing factor polypyrimidine tract binding protein (PTBP1/hnRNP I), the mRNA export factor THO complex subunit 4 (ALY/THOC4), and the 3' end cleavage stimulation factor 64 kDa (CSTF2). We observed interactions at promoters, internal exons, and 3' ends of active genes. PTBP1 had biases toward promoters and often coincided with RNA polymerase II (RNA Pol II). The 3' processing factor, CSTF2, had biases toward 3' ends but was also observed at promoters. The mRNA processing and export factor, ALY, mapped to some exons but predominantly localized to introns and did not coincide with RNA Pol II. Because the RNA binding proteins did not consistently coincide with RNA Pol II, the data support a processing mechanism driven by reorganization of transcription complexes as opposed to a scanning mechanism. In sum, we present the mapping in mammalian cells of RNA binding proteins across a portion of the genome that provides insight into the transcriptional assembly of RNA-protein complexes.