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We developed an efficient and accurate computational framework, RABIT (regression analysis with background integration), and comprehensively integrated public transcription factor (TF)-binding profiles with TCGA tumor-profiling datasets in 18 cancer types. To systematically search for cancer-associated TFs, RABIT controls the effect of tumor-confounding factors on transcriptional regulation, such as copy number alteration, DNA methylation, and TF somatic mutation. Our predicted TF regulatory activity in tumors is highly consistent with the knowledge from cancer gene databases and reveals many previously unidentified cancer-associated TFs. We also analyzed RNA-binding protein regulation in cancer and demonstrated that RABIT is a general platform for predicting oncogenic gene expression regulators.

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.

Human neurons are functional over an entire lifetime, yet the mechanisms that preserve function and protect against neurodegeneration during ageing are unknown. Here we show that induction of the repressor element 1-silencing transcription factor (REST; also known as neuron-restrictive silencer factor, NRSF) is a universal feature of normal ageing in human cortical and hippocampal neurons. REST is lost, however, in mild cognitive impairment and Alzheimer’s disease. Chromatin immunoprecipitation with deep sequencing and expression analysis show that REST represses genes that promote cell death and Alzheimer’s disease pathology, and induces the expression of stress response genes. Moreover, REST potently protects neurons from oxidative stress and amyloid β-protein toxicity, and conditional deletion of REST in the mouse brain leads to age-related neurodegeneration. A functional orthologue of REST, Caenorhabditis elegans SPR-4, also protects against oxidative stress and amyloid β-protein toxicity. During normal ageing, REST is induced in part by cell non-autonomous Wnt signalling. However, in Alzheimer’s disease, frontotemporal dementia and dementia with Lewy bodies, REST is lost from the nucleus and appears in autophagosomes together with pathological misfolded proteins. Finally, REST levels during ageing are closely correlated with cognitive preservation and longevity. Thus, the activation state of REST may distinguish neuroprotection from neurodegeneration in the ageing brain.

The androgen receptor (AR) is a key factor that regulates the behavior and fate of prostate cancer cells. The AR-regulated network is activated when AR binds enhancer elements and modulates specific enhancer–promoter looping. Kallikrein-related peptidase 3 (KLK3), which codes for prostate-specific antigen (PSA), is a well-known AR-regulated gene and its upstream enhancers produce bidirectional enhancer RNAs (eRNAs), termed KLK3e. Here, we demonstrate that KLK3e facilitates the spatial interaction of the KLK3 enhancer and the KLK2 promoter and enhances long-distance KLK2 transcriptional activation. KLK3e carries the core enhancer element derived from the androgen response element III (ARE III), which is required for the interaction of AR and Mediator 1 (Med1). Furthermore, we show that KLK3e processes RNA-dependent enhancer activity depending on the integrity of core enhancer elements. The transcription of KLK3e was detectable and its expression is significantly correlated with KLK3 \((R^2 = 0.6213, P < 5 × 10^{−11})\) and KLK2 \((R^2 = 0.5893, P < 5 × 10^{−10})\) in human prostate tissues. Interestingly, RNAi silencing of KLK3e resulted in a modest negative effect on prostate cancer cell proliferation. Accordingly, we report that an androgen-induced eRNA scaffolds the AR-associated protein complex that modulates chromosomal architecture and selectively enhances AR-dependent gene expression.

Tissues may adopt diverse strategies to establish specific transcriptional programs in daughter lineages. In intestinal crypts, enhancers for genes expressed in both major cell types appear broadly permissive in stem and specified progenitor cells. In blood, another self-renewing tissue, it is unclear when chromatin becomes permissive for transcription of genes expressed in distinct terminal lineages. Using chromatin immunoprecipitation (ChIP) combined with deep sequencing (ChIP-seq) to profile activating histone marks, we studied enhancer dynamics in primary mouse blood stem, progenitor, and specified cells. Stem and multipotent progenitor cells show scant H3K4me2 marking at enhancers bound by specific transcription factors in their committed progeny. Rather, enhancers are modulated dynamically and serially, with substantial loss and gain of H3K4me2, at each cellular transition. Quantitative analysis of these dynamics accurately modeled hematopoiesis according to Waddington’s notion of epigenotypes. Delineation of enhancers in terminal blood lineages coincides with cell specification, and enhancers active in single lineages show well-positioned H3K4me2- and H3K27ac-marked nucleosomes and DNaseI hypersensitivity in other cell types, revealing limited lineage fidelity. These findings demonstrate that enhancer chronology in blood cells differs markedly from that in intestinal crypts. Chromatin dynamics in hematopoiesis provide a useful foundation to consider classical observations such as cellular reprogramming and multilineage locus priming.

We propose a statistical algorithm MethylPurify that uses regions with bisulfite reads showing discordant methylation levels to infer tumor purity from tumor samples alone. MethylPurify can identify differentially methylated regions (DMRs) from individual tumor methylome samples, without genomic variation information or prior knowledge from other datasets. In simulations with mixed bisulfite reads from cancer and normal cell lines, MethylPurify correctly inferred tumor purity and identified over 96% of the DMRs. From patient data, MethylPurify gave satisfactory DMR calls from tumor methylome samples alone, and revealed potential missed DMRs by tumor to normal comparison due to tumor heterogeneity. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0419-x) contains supplementary material, which is available to authorized users.

Lineage-restricted transcription factors (TFs) are frequently mutated or overexpressed in cancer and contribute toward malignant behaviors, but the molecular bases of their oncogenic properties are largely unknown. Because TF activities are difficult to inhibit directly with small molecules, the genes and pathways they regulate might represent more tractable targets for drug therapy. We studied GATA6, a TF gene that is frequently amplified or overexpressed in gastric, esophageal, and pancreatic adenocarcinomas. GATA6-overexpressing gastric cancer cell lines cluster in gene expression space, separate from non-overexpressing lines. This expression clustering signifies a shared pathogenic group of genes that GATA6 may regulate through direct cis-element binding. We used chromatin immunoprecipation and sequencing (ChIP-seq) to identify GATA6-bound genes and considered TF occupancy in relation to genes that respond to GATA6 depletion in cell lines and track with GATA6 mRNA (synexpression groups) in primary gastric cancers. Among other cellular functions, GATA6-occupied genes control apoptosis and govern M-phase of the cell cycle. Depletion of GATA6 reduced levels of the latter transcripts and arrested cells in G2 and M phases of the cell cycle. Synexpression in human tumor samples identified likely direct transcriptional targets substantially better than consideration only of transcripts that respond to GATA6 loss in cultured cells. Candidate target genes responded to loss of GATA6 or its homolog GATA4 and even more to depletion of both proteins. Many GATA6-dependent genes lacked nearby binding sites but several strongly dependent, synexpressed, and GATA6-bound genes encode TFs such as MYC, HES1, RARB, and CDX2. Thus, many downstream effects occur indirectly through other TFs and GATA6 activity in gastric cancer is partially redundant with GATA4. This integrative analysis of locus occupancy, gene dependency, and synexpression provides a functional signature of GATA6-overexpressing gastric cancers, revealing both limits and new therapeutic directions for a challenging and frequently fatal disease.

Tissue-specific gene expression requires modulation of nucleosomes, allowing transcription factors to occupy cis elements that are accessible only in selected tissues. Master transcription factors control cell-specific genes and define cellular identities, but it is unclear if they possess special abilities to regulate cell-specific chromatin and if such abilities might underlie lineage determination and maintenance. One prevailing view is that several transcription factors enable chromatin access in combination. The homeodomain protein CDX2 specifies the embryonic intestinal epithelium, through unknown mechanisms, and partners with transcription factors such as HNF4A in the adult intestine. We examined enhancer chromatin and gene expression following Cdx2 or Hnf4a excision in mouse intestines. HNF4A loss did not affect CDX2 binding or chromatin, whereas CDX2 depletion modified chromatin significantly at CDX2-bound enhancers, disrupted HNF4A occupancy, and abrogated expression of neighboring genes. Thus, CDX2 maintains transcription-permissive chromatin, illustrating a powerful and dominant effect on enhancer configuration in an adult tissue. Similar, hierarchical control of cell-specific chromatin states is probably a general property of master transcription factors.

Histone modifications play important roles in regulating eukaryotic gene expression and have been used to model expression levels. Here, we present a regression model to systematically infer mRNA stability by comparing transcriptome profiles with ChIP-seq of H3K4me3, H3K27me3 and H3K36me3. The results from multiple human and mouse cell lines show that the inferred unstable mRNAs have significantly longer 3′Untranslated Regions (UTRs) and more microRNA binding sites within 3′UTR than the inferred stable mRNAs. Regression residuals derived from RNA-seq, but not from GRO-seq, are highly correlated with the half-lives measured by pulse-labeling experiments, supporting the rationale of our inference. Whereas, the functions enriched in the inferred stable and unstable mRNAs are consistent with those from pulse-labeling experiments, we found the unstable mRNAs have higher cell-type specificity under functional constraint. We conclude that the systematical use of histone modifications can differentiate non-expressed mRNAs from unstable mRNAs, and distinguish stable mRNAs from highly expressed ones. In summary, we represent the first computational model of mRNA stability inference that compares transcriptome and epigenome profiles, and provides an alternative strategy for directing experimental measurements.

Motivation: With the rapid development of high-throughput sequencing technologies, the genome-wide profiling of nucleosome positioning has become increasingly affordable. Many future studies will investigate the dynamic behaviour of nucleosome positioning in cells that have different states or that are exposed to different conditions. However, a robust method to effectively identify the regions of differential nucleosome positioning (RDNPs) has not been previously available. Results:: We describe a novel computational approach, DiNuP, that compares nucleosome profiles generated by high-throughput sequencing under various conditions. DiNuP provides a statistical P-value for each identified RDNP based on the difference of read distributions. DiNuP also empirically estimates the false discovery rate as a cutoff when two samples have different sequencing depths and differentiate reliable RDNPs from the background noise. Evaluation of DiNuP showed it to be both sensitive and specific for the detection of changes in nucleosome location, occupancy and fuzziness. RDNPs that were identified using publicly available datasets revealed that nucleosome positioning dynamics are closely related to the epigenetic regulation of transcription. Availability and implementation: DiNuP is implemented in Python and is freely available at http://www.tongji.edu.cn/~zhanglab/DiNuP.

We performed a systematic evaluation of how variations in sequencing depth and other parameters influence interpretation of Chromatin immunoprecipitation (ChIP) followed by sequencing (ChIP-seq) experiments. Using Drosophila S2 cells, we generated ChIP-seq datasets for a site-specific transcription factor (Suppressor of Hairy-wing) and a histone modification (H3K36me3). We detected a chromatin state bias, open chromatin regions yielded higher coverage, which led to false positives if not corrected and had a greater effect on detection specificity than any base-composition bias. Paired-end sequencing revealed that single-end data underestimated ChIP library complexity at high coverage. The removal of reads originating at the same base reduced false-positives while having little effect on detection sensitivity. Even at a depth of ~1 read/bp coverage of mappable genome, ~1% of the narrow peaks detected on a tiling array were missed by ChIP-seq. Evaluation of widely-used ChIP-seq analysis tools suggests that adjustments or algorithm improvements are required to handle datasets with deep coverage.

Transcription factors that potently induce cell fate often remain expressed in the induced organ throughout life, but their requirements in adults are uncertain and varied. Mechanistically, it is unclear if they activate only tissue-specific genes or also directly repress heterologous genes. We conditionally inactivated mouse Cdx2, a dominant regulator of intestinal development, and mapped its genome occupancy in adult intestinal villi. Although homeotic transformation, observed in Cdx2-null embryos, was absent in mutant adults, gene expression and cell morphology were vitally compromised. Lethality was significantly accelerated in mice lacking both Cdx2 and its homolog Cdx1, with particular exaggeration of defects in villus enterocyte differentiation. Importantly, Cdx2 occupancy correlated with hundreds of transcripts that fell but not with equal numbers that rose with Cdx loss, indicating a predominantly activating role at intestinal cis-regulatory regions. Integrated consideration of a transcription factor's mutant phenotype and cistrome hence reveals the continued and distinct requirement in adults of a critical developmental regulator that activates tissue-specific genes.

The ChIP-chip and ChIP-seq techniques enable genome-wide mapping of in vivo protein-DNA interactions and chromatin states. The cross-platform and between-laboratory variation poses a challenge to the comparison and integration of results from different ChIP experiments. We describe a novel method, MM-ChIP, which integrates information from cross-platform and between-laboratory ChIP-chip or ChIP-seq datasets. It improves both the sensitivity and the specificity of detecting ChIP-enriched regions, and is a useful meta-analysis tool for driving discoveries from multiple data sources.

MicroRNAs (miRNAs) are a class of 20–23 nucleotide small RNAs that regulate gene expression post-transcriptionally in animals and plants. Annotation of miRNAs by the miRNA database (miRBase) has largely relied on computational approaches. As a result, many miRBase entries lack experimental validation, and discrepancies between miRBase annotation and actual miRNA sequences are often observed. In this study, we integrated the small RNA sequencing (smRNA-seq) datasets in Caenorhabditis elegans and Drosophila melanogaster and devised an analytical pipeline coupled with detailed manual inspection to curate miRNA annotation systematically in miRBase. Our analysis reveals 19 (17.0%) and 51 (31.3%) miRNAs entries with detectable smRNA-seq reads have mature sequence discrepancies in C. elegans and D. melanogaster, respectively. These discrepancies frequently occur either for conserved miRNA families whose mature sequences were predicted according to their homologous counterparts in other species or for miRNAs whose precursor miRNA (pre-miRNA) hairpins produce an abundance of multiple miRNA isoforms or variants. Our analysis shows that while Drosophila pre-miRNAs, on average, produce less than 60% accurate mature miRNA reads in addition to their 5′ and 3′ variant isoforms, the precision of miRNA processing in C. elegans is much higher, at over 90%. Based on the revised miRNA sequences, we analyzed expression patterns of the more conserved (MC) and less conserved (LC) miRNAs and found that, whereas MC miRNAs are often co-expressed at multiple developmental stages, LC miRNAs tend to be expressed specifically at fewer stages.

Cell differentiation requires remodeling of tissue-specific gene loci and activities of key transcriptional regulators, which are recognized for their dominant control over cellular programs. Using epigenomic methods, we characterized enhancer elements specifically modified in differentiating intestinal epithelial cells and found enrichment of transcription factor-binding motifs corresponding to CDX2, a critical regulator of the intestine. Directed investigation revealed surprising lability in CDX2 occupancy of the genome, with redistribution from hundreds of sites occupied only in proliferating cells to thousands of new sites in differentiated cells. Knockout mice confirmed distinct Cdx2 requirements in dividing and mature adult intestinal cells, including responsibility for the active enhancer configuration associated with maturity. Dynamic CDX2 occupancy corresponds with condition-specific gene expression and, importantly, to differential co-occupancy with other tissue-restricted transcription factors such as GATA6 and HNF4A. These results reveal dynamic, context-specific functions and mechanisms of a prominent transcriptional regulator within a cell lineage.

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.

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.

A novel normalization method based on the GC content of probes is developed for two-color tiling arrays. The proposed method, together with robust estimates of the model parameters, is shown to perform superbly on published data sets. A robust algorithm for detecting peak regions is also formulated and shown to perform well compared to other approaches. The tools have been implemented as a stand-alone Java program called MA2C, which can display various plots of statistical analysis for quality control., Statistics

Background: Transcription by RNA polymerase II is regulated at many steps including initiation, promoter release, elongation and termination. Accumulation of RNA polymerase II at particular locations across genes can be indicative of sites of regulation. RNA polymerase II is thought to accumulate at the promoter and at sites of co-transcriptional alternative splicing where the rate of RNA synthesis slows. Results: To further understand transcriptional regulation at a global level, we determined the distribution of RNA polymerase II within regions of the human genome designated by the ENCODE project. Hypophosphorylated RNA polymerase II localizes almost exclusively to 5' ends of genes. On the other hand, localization of total RNA polymerase II reveals a variety of distinct landscapes across many genes with 74% of the observed enriched locations at exons. RNA polymerase II accumulates at many annotated constitutively spliced exons, but is biased for alternatively spliced exons. Finally, RNA polymerase II is also observed at locations not in gene regions. Conclusion: Localizing RNA polymerase II across many millions of base pairs in the human genome identifies novel sites of transcription and provides insights into the regulation of transcription elongation. These data indicate that RNA polymerase II accumulates most often at exons during transcription. Thus, a major factor of transcription elongation control in mammalian cells is the coordination of transcription and pre-mRNA processing to define exons.

The identification of regulatory motifs is important for the study of gene expression. Here we present a suite of programs that we have developed to search for regulatory sequence motifs: (i) BioProspector, a Gibbs-sampling-based program for predicting regulatory motifs from co-regulated genes in prokaryotes or lower eukaryotes; (ii) CompareProspector, an extension to BioProspector which incorporates comparative genomics features to be used for higher eukaryotes; (iii) MDscan, a program for finding protein–DNA interaction sites from ChIP-on-chip targets. All three programs examine a group of sequences that may share common regulatory motifs and output a list of putative motifs as position-specific probability matrices, the individual sites used to construct the motifs and the location of each site on the input sequences. The web servers and executables can be accessed at http://seqmotifs.stanford.edu.

We propose motif regressor for discovering sequence motifs upstream of genes that undergo expression changes in a given condition. The method combines the advantages of matrix-based motif finding and oligomer motif-expression regression analysis, resulting in high sensitivity and specificity. motif regressor is particularly effective in discovering expression-mediating motifs of medium to long width with multiple degenerate positions. When applied to Saccharomyces cerevisiae, motif regressor identified the ROX1 and YAP1 motifs from Rox1p and Yap1p overexpression experiments, respectively; predicted that Gcn4p may have increased activity in YAP1 deletion mutants; reported a group of motifs (including GCN4, PHO4, MET4, STRE, USR1, RAP1, M3A, and M3B) that may mediate the transcriptional response to amino acid starvation; and found all of the known cell-cycle regulation motifs from 18 expression microarrays over two cell cycles.