A quantitative model of transcriptional regulation reveals the influence of binding location on expression

Peak Scores Significantly Depend on the Relationships between Contextual Signals in ChIP-Seq Peaks

Chromatin immunoprecipitation followed by massively parallel DNA sequencing (ChIP-seq) is a central genome-wide method for in vivo analyses of DNA-protein interactions in various cellular conditions. Numerous studies have demonstrated the complex contextual organization of ChIP-seq peak sequences and the presence of binding sites for transcription factors in them. We assessed the dependence of the ChIP-seq peak score on the presence of different contextual signals in the peak sequences by analyzing these sequences from several ChIP-seq experiments using our fully enumerative GPU-based de novo motif discovery method, Argo_CUDA. Analysis revealed sets of significant IUPAC motifs corresponding to the binding sites of the target and partner transcription factors. For these ChIP-seq experiments, multiple regression models were constructed, demonstrating a significant dependence of the peak scores on the presence in the peak sequences of not only highly significant target motifs but also less significant motifs corresponding to the binding sites of the partner transcription factors. A significant correlation was shown between the presence of the target motifs FOXA2 and the partner motifs HNF4G, which found experimental confirmation in the scientific literature, demonstrating the important contribution of the partner transcription factors to the binding of the target transcription factor to DNA and, consequently, their important contribution to the peak score.

Topoisomerase IIA in adult NSCs regulates SVZ neurogenesis by transcriptional activation of Usp37

Topoisomerase IIA (TOP2a) has traditionally been known as an important nuclear enzyme that resolves entanglements and relieves torsional stress of DNA double strands. However, its function in genomic transcriptional regulation remains largely unknown, especially during adult neurogenesis. Here, we show that TOP2a is preferentially expressed in neurogenic niches in the brain of adult mice, such as the subventricular zone (SVZ). Conditional knockout of Top2a in adult neural stem cells (NSCs) of the SVZ significantly inhibits their self-renewal and proliferation, and ultimately reduces neurogenesis. To gain insight into the molecular mechanisms by which TOP2a regulates adult NSCs, we perform RNA-sequencing (RNA-Seq) plus chromatin immunoprecipitation sequencing (ChIP-Seq) and identify ubiquitin-specific protease 37 (Usp37) as a direct TOP2a target gene. Importantly, overexpression of Usp37 is sufficient to rescue the impaired self-renewal ability of adult NSCs caused by Top2a knockdown. Taken together, this proof-of-principle study illustrates a TOP2a/Usp37-mediated novel molecular mechanism in adult neurogenesis, which will significantly expand our understanding of the function of topoisomerase in the adult brain.

Arid1a regulates cell cycle exit of transit-amplifying cells by inhibiting the Aurka-Cdk1 axis in mouse incisor

Stem cells self-renew or give rise to transit-amplifying cells (TACs) that differentiate into specific functional cell types. The fate determination of stem cells to TACs and their transition to fully differentiated progeny is precisely regulated to maintain tissue homeostasis. Arid1a, a core component of the switch/sucrose nonfermentable complex, performs epigenetic regulation of stage- and tissue-specific genes that is indispensable for stem cell homeostasis and differentiation. However, the functional mechanism of Arid1a in the fate commitment of mesenchymal stem cells (MSCs) and their progeny is not clear. Using the continuously growing adult mouse incisor model, we show that Arid1a maintains tissue homeostasis through limiting proliferation, promoting cell cycle exit and differentiation of TACs by inhibiting the Aurka-Cdk1 axis. Loss of Arid1a overactivates the Aurka-Cdk1 axis, leading to expansion of the mitotic TAC population but compromising their differentiation ability. Furthermore, the defective homeostasis after loss of Arid1a ultimately leads to reduction of the MSC population. These findings reveal the functional significance of Arid1a in regulating the fate of TACs and their interaction with MSCs to maintain tissue homeostasis.

Estrogen Receptor, Inflammatory, and FOXO Transcription Factors Regulate Expression of Myasthenia Gravis-Associated Circulating microRNAs

MicroRNAs (miRNAs) are small non-coding RNA molecules that regulate important intracellular biological processes. In myasthenia gravis (MG), a disease-specific pattern of elevated circulating miRNAs has been found, and proposed as potential biomarkers. These elevated miRNAs include miR-150-5p, miR-21-5p, and miR-30e-5p in acetylcholine receptor antibody seropositive (AChR+) MG and miR-151a-3p, miR-423-5p, let-7a-5p, and let-7f-5p in muscle-specific tyrosine kinase antibody seropositive (MuSK+) MG. In this study, we examined the regulation of each of these miRNAs using chromatin immunoprecipitation sequencing (ChIP-seq) data from the Encyclopedia of DNA Elements (ENCODE) to gain insight into the transcription factor pathways that drive their expression in MG. Our aim was to look at the transcription factors that regulate miRNAs and then validate some of those in vivo with cell lines that have sufficient expression of these transcription factors This analysis revealed several transcription factor families that regulate MG-specific miRNAs including the Forkhead box or the FOXO proteins (FoxA1, FoxA2, FoxM1, FoxP2), AP-1, interferon regulatory factors (IRF1, IRF3, IRF4), and signal transducer and activator of transcription proteins (Stat1, Stat3, Stat5a). We also found binding sites for nuclear factor of activated T-cells (NFATC1), nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB), early growth response factor (EGR1), and the estrogen receptor 1 (ESR1). AChR+ MG miRNAs showed a stronger overall regulation by the FOXO transcription factors, and of this group, miR-21-5p, let-7a, and let 7f were found to possess ESR1 binding sites. Using a murine macrophage cell line, we found activation of NF-κB -mediated inflammation by LPS induced expression of miR-21-5p, miR-30e-5p, miR-423-5p, let-7a, and let-7f. Pre-treatment of cells with the anti-inflammatory drugs prednisone or deflazacort attenuated induction of inflammation-induced miRNAs. Interestingly, the activation of inflammation induced packaging of the AChR+-specific miRNAs miR-21-5p and miR-30e-5p into exosomes, suggesting a possible mechanism for the elevation of these miRNAs in MG patient serum. In conclusion, our study summarizes the regulatory transcription factors that drive expression of AChR+ and MuSK+ MG-associated miRNAs. Our findings of elevated miR-21-5p and miR-30e-5p expression in immune cells upon inflammatory stimulation and the suppressive effect of corticosteroids strengthens the putative role of these miRNAs in the MG autoimmune response.

Lessons from eRNAs: understanding transcriptional regulation through the lens of nascent RNAs

Nascent transcription assays, such as global run-on sequencing (GRO-seq) and precision run-on sequencing (PRO-seq), have uncovered a myriad of unstable RNAs being actively produced from numerous sites genome-wide. These transcripts provide a more complete and immediate picture of the impact of regulatory events. Transcription factors recruit RNA polymerase II, effectively initiating the process of transcription; repressors inhibit polymerase recruitment. Efficiency of recruitment is dictated by sequence elements in and around the RNA polymerase loading zone. A combination of sequence elements and RNA binding proteins subsequently influence the ultimate stability of the resulting transcript. Some of these transcripts are capable of providing feedback on the process, influencing subsequent transcription. By monitoring RNA polymerase activity, nascent assays provide insights into every step of the regulated process of transcription.

Modelling the gene expression and the DNA-binding in the 3T3-L1 differentiating adipocytes

The 3T3-L1 pre-adipocyte cell line is widely used to study the fat cell differentiation in vitro. Researchers also use this cell model to study obesity and insulin resistance. We surveyed the literature, the gene expression omnibus and the sequence read archive for RNA-Seq and ChIP-Seq datasets of MDI-induced 3T3-L1 differentiating cells sampled at one or more time points. The metadata of the relevant datasets were manually curated using unified language across the original studies. The raw reads were collected and pre-processed using a reproducible state-of-the-art pipeline. The final datasets are presented as reads count in genes for the RNA-Seq and reads count in peaks for the ChIP-Seq dataset. The curated datasets are available as two Bioconductor experimental data packages curatedAdipoRNA and curatedAdipoChIP. In addition, the packages document the source code of the data collection and the pre-processing pipelines. Here, we provide a descriptive analysis of the datasets with context and technical validation.

Early epigenomic and transcriptional changes reveal Elk-1 transcription factor as a therapeutic target in Huntington's disease

Huntington's disease (HD) is a chronic neurodegenerative disorder characterized by a late clinical onset despite ubiquitous expression of the mutant Huntingtin gene (HTT) from birth. Transcriptional dysregulation is a pivotal feature of HD. Yet, the genes that are altered in the prodromal period and their regulators, which present opportunities for therapeutic intervention, remain to be elucidated. Using transcriptional and chromatin profiling, we found aberrant transcription and changes in histone H3K27acetylation in the striatum of R6/1 mice during the presymptomatic disease stages. Integrating these data, we identified the Elk-1 transcription factor as a candidate regulator of prodromal changes in HD. Exogenous expression of Elk-1 exerted beneficial effects in a primary striatal cell culture model of HD, and adeno-associated virus-mediated Elk-1 overexpression alleviated transcriptional dysregulation in R6/1 mice. Collectively, our work demonstrates that aberrant gene expression precedes overt disease onset in HD, identifies the Elk-1 transcription factor as a key regulator linked to early epigenetic and transcriptional changes in HD, and presents evidence for Elk-1 as a target for alleviating molecular pathology in HD.

Genome-Wide Identification of Direct RTA Targets Reveals Key Host Factors for Kaposi's Sarcoma-Associated Herpesvirus Lytic Reactivation

Kaposi's sarcoma-associated herpesvirus (KSHV) is a human oncogenic virus, which maintains the persistent infection of the host by intermittently reactivating from latently infected cells to produce viral progenies. While it is established that the replication and transcription activator (RTA) viral transcription factor is required for the induction of lytic viral genes for KSHV lytic reactivation, it is still unknown to what extent RTA alters the host transcriptome to promote KSHV lytic cycle and viral pathogenesis. To address this question, we performed a comprehensive time course transcriptome analysis during KSHV reactivation in B-cell lymphoma cells and determined RTA-binding sites on both the viral and host genomes, which resulted in the identification of the core RTA-induced host genes (core RIGs). We found that the majority of RTA-binding sites at core RIGs contained the canonical RBP-Jκ-binding DNA motif. Subsequently, we demonstrated the vital role of the Notch signaling transcription factor RBP-Jκ for RTA-driven rapid host gene induction, which is consistent with RBP-Jκ being essential for KSHV lytic reactivation. Importantly, many of the core RIGs encode plasma membrane proteins and key regulators of signaling pathways and cell death; however, their contribution to the lytic cycle is largely unknown. We show that the cell cycle and chromatin regulator geminin and the plasma membrane protein gamma-glutamyltransferase 6, two of the core RIGs, are required for efficient KSHV reactivation and virus production. Our results indicate that host genes that RTA rapidly and directly induces can be pivotal for driving the KSHV lytic cycle.IMPORTANCE The lytic cycle of KSHV is involved not only in the dissemination of the virus but also viral oncogenesis, in which the effect of RTA on the host transcriptome is still unclear. Using genomics approaches, we identified a core set of host genes which are rapidly and directly induced by RTA in the early phase of KSHV lytic reactivation. We found that RTA does not need viral cofactors but requires its host cofactor RBP-Jκ for inducing many of its core RIGs. Importantly, we show a critical role for two of the core RIGs in efficient lytic reactivation and replication, highlighting their significance in the KSHV lytic cycle. We propose that the unbiased identification of RTA-induced host genes can uncover potential therapeutic targets for inhibiting KSHV replication and viral pathogenesis.

Impaired DNA demethylation of C/EBP sites causes premature aging

Here, Schäfer et al. investigated whether DNA methylation alterations are involved in aging. Using knockout mice for adapter proteins for site-specific demethylation by TET methylcytosine dioxygenases Gadd45a and Ing1, they show that enhancer methylation can affect aging and imply that C/EBP proteins play an unexpected role in this process.

Changes in DNA methylation are among the best-documented epigenetic alterations accompanying organismal aging. However, whether and how altered DNA methylation is causally involved in aging have remained elusive. GADD45α (growth arrest and DNA damage protein 45A) and ING1 (inhibitor of growth family member 1) are adapter proteins for site-specific demethylation by TET (ten-eleven translocation) methylcytosine dioxygenases. Here we show that Gadd45a/Ing1 double-knockout mice display segmental progeria and phenocopy impaired energy homeostasis and lipodystrophy characteristic of Cebp (CCAAT/enhancer-binding protein) mutants. Correspondingly, GADD45α occupies C/EBPβ/δ-dependent superenhancers and, cooperatively with ING1, promotes local DNA demethylation via long-range chromatin loops to permit C/EBPβ recruitment. The results indicate that enhancer methylation can affect aging and imply that C/EBP proteins play an unexpected role in this process. Our study suggests a causal nexus between DNA demethylation, metabolism, and organismal aging.

Regulation of circadian clock transcriptional output by CLOCK:BMAL1

The mammalian circadian clock relies on the transcription factor CLOCK:BMAL1 to coordinate the rhythmic expression of 15% of the transcriptome and control the daily regulation of biological functions. The recent characterization of CLOCK:BMAL1 cistrome revealed that although CLOCK:BMAL1 binds synchronously to all of its target genes, its transcriptional output is highly heterogeneous. By performing a meta-analysis of several independent genome-wide datasets, we found that the binding of other transcription factors at CLOCK:BMAL1 enhancers likely contribute to the heterogeneity of CLOCK:BMAL1 transcriptional output. While CLOCK:BMAL1 rhythmic DNA binding promotes rhythmic nucleosome removal, it is not sufficient to generate transcriptionally active enhancers as assessed by H3K27ac signal, RNA Polymerase II recruitment, and eRNA expression. Instead, the transcriptional activity of CLOCK:BMAL1 enhancers appears to rely on the activity of ubiquitously expressed transcription factors, and not tissue-specific transcription factors, recruited at nearby binding sites. The contribution of other transcription factors is exemplified by how fasting, which effects several transcription factors but not CLOCK:BMAL1, either decreases or increases the amplitude of many rhythmically expressed CLOCK:BMAL1 target genes. Together, our analysis suggests that CLOCK:BMAL1 promotes a transcriptionally permissive chromatin landscape that primes its target genes for transcription activation rather than directly activating transcription, and provides a new framework to explain how environmental or pathological conditions can reprogram the rhythmic expression of clock-controlled genes.

Identifying novel transcription factors involved in the inflammatory response by using binding site motif scanning in genomic regions defined by histone acetylation

The innate immune response to pathogenic challenge is a complex, multi-staged process involving thousands of genes. While numerous transcription factors that act as master regulators of this response have been identified, the temporal complexity of gene expression changes in response to pathogen-associated molecular pattern receptor stimulation strongly suggest that additional layers of regulation remain to be uncovered. The evolved pathogen response program in mammalian innate immune cells is understood to reflect a compromise between the probability of clearing the infection and the extent of tissue damage and inflammatory sequelae it causes. Because of that, a key challenge to delineating the regulators that control the temporal inflammatory response is that an innate immune regulator that may confer a selective advantage in the wild may be dispensable in the lab setting. In order to better understand the complete transcriptional response of primary macrophages to the bacterial endotoxin lipopolysaccharide (LPS), we designed a method that integrates temporally resolved gene expression and chromatin-accessibility measurements from mouse macrophages. By correlating changes in transcription factor binding site motif enrichment scores, calculated within regions of accessible chromatin, with the average temporal expression profile of a gene cluster, we screened for transcriptional factors that regulate the cluster. We have validated our predictions of LPS-stimulated transcriptional regulators using ChIP-seq data for three transcription factors with experimentally confirmed functions in innate immunity. In addition, we predict a role in the macrophage LPS response for several novel transcription factors that have not previously been implicated in immune responses. This method is applicable to any experimental situation where temporal gene expression and chromatin-accessibility data are available.

Navigating the Functional Landscape of Transcription Factors via Non-Negative Tensor Factorization Analysis of MEDLINE Abstracts

In this study, we developed and evaluated a novel text-mining approach, using non-negative tensor factorization (NTF), to simultaneously extract and functionally annotate transcriptional modules consisting of sets of genes, transcription factors (TFs), and terms from MEDLINE abstracts. A sparse 3-mode term × gene × TF tensor was constructed that contained weighted frequencies of 106,895 terms in 26,781 abstracts shared among 7,695 genes and 994 TFs. The tensor was decomposed into sub-tensors using non-negative tensor factorization (NTF) across 16 different approximation ranks. Dominant entries of each of 2,861 sub-tensors were extracted to form term–gene–TF annotated transcriptional modules (ATMs). More than 94% of the ATMs were found to be enriched in at least one KEGG pathway or GO category, suggesting that the ATMs are functionally relevant. One advantage of this method is that it can discover potentially new gene–TF associations from the literature. Using a set of microarray and ChIP-Seq datasets as gold standard, we show that the precision of our method for predicting gene–TF associations is significantly higher than chance. In addition, we demonstrate that the terms in each ATM can be used to suggest new GO classifications to genes and TFs. Taken together, our results indicate that NTF is useful for simultaneous extraction and functional annotation of transcriptional regulatory networks from unstructured text, as well as for literature based discovery. A web tool called Transcriptional Regulatory Modules Extracted from Literature (TREMEL), available at http://binf1.memphis.edu/tremel, was built to enable browsing and searching of ATMs.

Associating transcription factors and conserved RNA structures with gene regulation in the human brain

Anatomical subdivisions of the human brain can be associated with different neuronal functions. This functional diversification is reflected by differences in gene expression. By analyzing post-mortem gene expression data from the Allen Brain Atlas, we investigated the impact of transcription factors (TF) and RNA secondary structures on the regulation of gene expression in the human brain. First, we modeled the expression of a gene as a linear combination of the expression of TFs. We devised an approach to select robust TF-gene interactions and to determine localized contributions to gene expression of TFs. Among the TFs with the most localized contributions, we identified EZH2 in the cerebellum, NR3C1 in the cerebral cortex and SRF in the basal forebrain. Our results suggest that EZH2 is involved in regulating ZIC2 and SHANK1 which have been linked to neurological diseases such as autism spectrum disorder. Second, we associated enriched regulatory elements inside differentially expressed mRNAs with RNA secondary structure motifs. We found a group of purine-uracil repeat RNA secondary structure motifs plus other motifs in neuron related genes such as ACSL4 and ERLIN2.

Identification of a functional enhancer variant within the chronic pancreatitis-associated SPINK1 c.101A>G (p.Asn34Ser)-containing haplotype

The haplotype harboring the SPINK1 c.101A>G (p.Asn34Ser) variant (also known as rs17107315:T>C) represents the most important heritable risk factor for idiopathic chronic pancreatitis identified to date. The causal variant contained within this risk haplotype has however remained stubbornly elusive. Herein, we set out to resolve this enigma by employing a hypothesis-driven approach. First, we searched for variants in strong linkage disequilibrium (LD) with rs17107315:T>C using HaploReg v4.1. Second, we identified two candidate SNPs by visual inspection of sequences spanning all 25 SNPs found to be in LD with rs17107315:T>C, guided by prior knowledge of pancreas-specific transcription factors and their cognate binding sites. Third, employing a novel cis-regulatory module (CRM)-guided approach to further filter the two candidate SNPs yielded a solitary candidate causal variant. Finally, combining data from phylogenetic conservation and chromatin accessibility, cotransfection transactivation experiments, and population genetic studies, we suggest that rs142703147:C>A, which disrupts a PTF1L-binding site within an evolutionarily conserved HNF1A-PTF1L CRM located ∼4 kb upstream of the SPINK1 promoter, contributes to the aforementioned chronic pancreatitis risk haplotype. Further studies are required not only to improve the characterization of this functional SNP but also to identify other functional components that might contribute to this high-risk haplotype.

Transcriptional regulatory logic of the diurnal cycle in the mouse liver

Many organisms exhibit temporal rhythms in gene expression that propel diurnal cycles in physiology. In the liver of mammals, these rhythms are controlled by transcription-translation feedback loops of the core circadian clock and by feeding-fasting cycles. To better understand the regulatory interplay between the circadian clock and feeding rhythms, we mapped DNase I hypersensitive sites (DHSs) in the mouse liver during a diurnal cycle. The intensity of DNase I cleavages cycled at a substantial fraction of all DHSs, suggesting that DHSs harbor regulatory elements that control rhythmic transcription. Using chromatin immunoprecipitation followed by DNA sequencing (ChIP-seq), we found that hypersensitivity cycled in phase with RNA polymerase II (Pol II) loading and H3K27ac histone marks. We then combined the DHSs with temporal Pol II profiles in wild-type (WT) and Bmal1-/- livers to computationally identify transcription factors through which the core clock and feeding-fasting cycles control diurnal rhythms in transcription. While a similar number of mRNAs accumulated rhythmically in Bmal1-/- compared to WT livers, the amplitudes in Bmal1-/- were generally lower. The residual rhythms in Bmal1-/- reflected transcriptional regulators mediating feeding-fasting responses as well as responses to rhythmic systemic signals. Finally, the analysis of DNase I cuts at nucleotide resolution showed dynamically changing footprints consistent with dynamic binding of CLOCK:BMAL1 complexes. Structural modeling suggested that these footprints are driven by a transient heterotetramer binding configuration at peak activity. Together, our temporal DNase I mappings allowed us to decipher the global regulation of diurnal transcription rhythms in the mouse liver.

Simvastatin-induced sphingosine 1-phosphate receptor 1 expression is KLF2-dependent in human lung endothelial cells

We have demonstrated that simvastatin and sphingosine 1−phosphate (S1P) both attenuate increased vascular permeability in preclinical models of acute respiratory distress syndrome. However, the underlying mechanisms remain unclear. As Krüppel-like factor 2 (KLF2) serves as a critical regulator for cellular stress response in endothelial cells (EC), we hypothesized that simvastatin enhances endothelial barrier function via increasing expression of the barrier-promoting S1P receptor, S1PR1, via a KLF2-dependent mechanism. S1PR1 luciferase reporter promoter activity in human lung artery EC (HPAEC) was tested after simvastatin (5 μM), and S1PR1 and KLF2 protein expression detected by immunoblotting. In vivo, transcription and expression of S1PR1 and KLF2 in mice lungs were detected by microarray profiling and immunoblotting after exposure to simvastatin (10 mg/kg). Endothelial barrier function was measured by trans-endothelial electrical resistance with the S1PR1 agonist FTY720-(S)-phosphonate. Both S1PR1 and KLF2 gene expression (mRNA, protein) were significantly increased by simvastatin in vitro and in vivo. S1PR1 promoter activity was significantly increased by simvastatin (P < 0.05), which was significantly attenuated by KLF2 silencing (siRNA). Simvastatin induced KLF2 recruitment to the S1PR1 promoter, and consequently, significantly augmented the effects of the S1PR1 agonist on EC barrier enhancement (P < 0.05), which was significantly attenuated by KLF2 silencing (P < 0.05). These results suggest that simvastatin upregulates S1PR1 transcription and expression via the transcription factor KLF2, and consequently augments the effects of S1PR1 agonists on preserving vascular barrier integrity. These results may lead to novel combinatorial therapeutic strategies for lung inflammatory syndromes.

Baf60b-mediated ATM-p53 activation blocks cell identity conversion by sensing chromatin opening

Lineage conversion by expression of lineage-specific transcription factors is a process of epigenetic remodeling that has low efficiency. The mechanism by which a cell resists lineage conversion is largely unknown. Using hepatic-specific transcription factors Foxa3, Hnf1α and Gata4 (3TF) to induce hepatic conversion in mouse fibroblasts, we showed that 3TF induced strong activation of the ATM-p53 pathway, which led to proliferation arrest and cell death, and it further prevented hepatic conversion. Notably, ATM activation, independent of DNA damage, responded to chromatin opening during hepatic conversion. By characterizing the early molecular events during hepatic conversion, we found that Baf60b, a member of the SWI/SNF chromatin remodeling complex, links chromatin opening to ATM activation by facilitating ATM recruitment to the open chromatin regions of a panel of hepatic gene loci. These findings shed light on cellular responses to lineage conversion by revealing a function of the ATM-p53 pathway in sensing chromatin opening.

Hyper- and hypo- nutrition studies of the hepatic transcriptome and epigenome suggest that PPARα regulates anaerobic glycolysis

Diet plays a crucial role in shaping human health and disease. Diets promoting obesity and insulin resistance can lead to severe metabolic diseases, while calorie-restricted (CR) diets can improve health and extend lifespan. In this work, we fed mice either a chow diet (CD), a 16 week high-fat diet (HFD), or a CR diet to compare and contrast the effects of these diets on mouse liver biology. We collected transcriptomic and epigenomic datasets from these mice using RNA-Seq and DNase-Seq. We found that both CR and HFD induce extensive transcriptional changes, in some cases altering the same genes in the same direction. We used our epigenomic data to infer transcriptional regulatory proteins bound near these genes that likely influence their expression levels. In particular, we found evidence for critical roles played by PPARα and RXRα. We used ChIP-Seq to profile the binding locations for these factors in HFD and CR livers. We found extensive binding of PPARα near genes involved in glycolysis/gluconeogenesis and uncovered a role for this factor in regulating anaerobic glycolysis. Overall, we generated extensive transcriptional and epigenomic datasets from livers of mice fed these diets and uncovered new functions and gene targets for PPARα.

Cancer somatic mutations cluster in a subset of regulatory sites predicted from the ENCODE data

Background

Transcriptional regulation of gene expression is essential for cellular differentiation and function, and defects in the process are associated with cancer. The ENCODE project has mapped potential regulatory sites across the complete genome in many cell types, and these regions have been shown to harbour many of the somatic mutations that occur in cancer cells, suggesting that their effects may drive cancer initiation and development. The ENCODE data suggests a very large number of regulatory sites, and methods are needed to identify those that are most relevant and to connect them to the genes that they control.

Methods

Predictive models of gene expression were developed by integrating the ENCODE data for regulation, including transcription factor binding and DNase1 hypersensitivity, with RNA-seq data for gene expression. A penalized regression method was used to identify the most predictive potential regulatory sites for each transcript. Known cancer somatic mutations from the COSMIC database were mapped to potential regulatory sites, and we examined differences in the mapping frequencies associated with sites chosen in regulatory models and other (rejected) sites. The effects of potential confounders, for example replication timing, were considered.

Results

Cancer somatic mutations preferentially occupy those regulatory regions chosen in our models as most predictive of gene expression.

Conclusion

Our methods have identified a significantly reduced set of regulatory sites that are enriched in cancer somatic mutations and are more predictive of gene expression. This has significance for the mechanistic interpretation of cancer mutations, and the understanding of genetic regulation.

Electronic supplementary material

The online version of this article (doi:10.1186/s12943-016-0560-0) contains supplementary material, which is available to authorized users.

REST regulation of gene networks in adult neural stem cells

Adult hippocampal neural stem cells generate newborn neurons throughout life due to their ability to self-renew and exist as quiescent neural progenitors (QNPs) before differentiating into transit-amplifying progenitors (TAPs) and newborn neurons. The mechanisms that control adult neural stem cell self-renewal are still largely unknown. Conditional knockout of REST (repressor element 1-silencing transcription factor) results in precocious activation of QNPs and reduced neurogenesis over time. To gain insight into the molecular mechanisms by which REST regulates adult neural stem cells, we perform chromatin immunoprecipitation sequencing and RNA-sequencing to identify direct REST target genes. We find REST regulates both QNPs and TAPs, and importantly, ribosome biogenesis, cell cycle and neuronal genes in the process. Furthermore, overexpression of individual REST target ribosome biogenesis or cell cycle genes is sufficient to induce activation of QNPs. Our data define novel REST targets to maintain the quiescent neural stem cell state.

The transcription factor REST plays a crucial role in maintaining the adult neural stem cell pool. To better understand how REST maintains quiescence in neural progenitors, the authors use ChIP-seq and RNA-seq and find that REST regulates represses ribosome biogenesis, cell cycle and neuronal genes.

iTAR: a web server for identifying target genes of transcription factors using ChIP-seq or ChIP-chip data

Background

Chromatin immunoprecipitation followed by massively parallel DNA sequencing (ChIP-seq) or microarray hybridization (ChIP-chip) has been widely used to determine the genomic occupation of transcription factors (TFs). We have previously developed a probabilistic method, called TIP (Target Identification from Profiles), to identify TF target genes using ChIP-seq/ChIP-chip data. To achieve high specificity, TIP applies a conservative method to estimate significance of target genes, with the trade-off being a relatively low sensitivity of target gene identification compared to other methods. Additionally, TIP’s output does not render binding-peak locations or intensity, information highly useful for visualization and general experimental biological use, while the variability of ChIP-seq/ChIP-chip file formats has made input into TIP more difficult than desired.

Description

To improve upon these facets, here we present are fined TIP with key extensions. First, it implements a Gaussian mixture model for p-value estimation, increasing target gene identification sensitivity and more accurately capturing the shape of TF binding profile distributions. Second, it enables the incorporation of TF binding-peak data by identifying their locations in significant target gene promoter regions and quantifies their strengths. Finally, for full ease of implementation we have incorporated it into a web server (http://syslab3.nchu.edu.tw/iTAR/) that enables flexibility of input file format, can be used across multiple species and genome assembly versions, and is freely available for public use. The web server additionally performs GO enrichment analysis for the identified target genes to reveal the potential function of the corresponding TF.

Conclusions

The iTAR web server provides a user-friendly interface and supports target gene identification in seven species, ranging from yeast to human. To facilitate investigating the quality of ChIP-seq/ChIP-chip data, the web server generates the chart of the characteristic binding profiles and the density plot of normalized regulatory scores. The iTAR web server is a useful tool in identifying TF target genes from ChIP-seq/ChIP-chip data and discovering biological insights.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-2963-0) contains supplementary material, which is available to authorized users.

A genome wide transcriptional model of the complex response to pre-TCR signalling during thymocyte differentiation

Developing thymocytes require pre-TCR signalling to differentiate from CD4-CD8- double negative to CD4+CD8+ double positive cell. Here we followed the transcriptional response to pre-TCR signalling in a synchronised population of differentiating double negative thymocytes. This time series analysis revealed a complex transcriptional response, in which thousands of genes were up and down-regulated before changes in cell surface phenotype were detected. Genome-wide measurement of RNA degradation of individual genes showed great heterogeneity in the rate of degradation between different genes. We therefore used time course expression and degradation data and a genome wide transcriptional modelling (GWTM) strategy to model the transcriptional response of genes up-regulated on pre-TCR signal transduction. This analysis revealed five major temporally distinct transcriptional activities that up regulate transcription through time, whereas down-regulation of expression occurred in three waves. Our model thus placed known regulators in a temporal perspective, and in addition identified novel candidate regulators of thymocyte differentiation.

Pathway-based network modeling finds hidden genes in shRNA screen for regulators of acute lymphoblastic leukemia

Data integration stands to improve interpretation of RNAi screens which, as a result of off-target effects, typically yield numerous gene hits of which only a few validate. These off-target effects can result from seed matches to unintended gene targets (reagent-based) or cellular pathways, which can compensate for gene perturbations (biology-based). We focus on the biology-based effects and use network modeling tools to discover pathways de novo around RNAi hits. By looking at hits in a functional context, we can uncover novel biology not identified from any individual 'omics measurement. We leverage multiple 'omic measurements using the Simultaneous Analysis of Multiple Networks (SAMNet) computational framework to model a genome scale shRNA screen investigating Acute Lymphoblastic Leukemia (ALL) progression in vivo. Our network model is enriched for cellular processes associated with hematopoietic differentiation and homeostasis even though none of the individual 'omic sets showed this enrichment. The model identifies genes associated with the TGF-beta pathway and predicts a role in ALL progression for many genes without this functional annotation. We further experimentally validate the hidden genes - Wwp1, a ubiquitin ligase, and Hgs, a multi-vesicular body associated protein - for their role in ALL progression. Our ALL pathway model includes genes with roles in multiple types of leukemia and roles in hematological development. We identify a tumor suppressor role for Wwp1 in ALL progression. This work demonstrates that network integration approaches can compensate for off-target effects, and that these methods can uncover novel biology retroactively on existing screening data. We anticipate that this framework will be valuable to multiple functional genomic technologies - siRNA, shRNA, and CRISPR - generally, and will improve the utility of functional genomic studies.

Changes in Gene Expression and Estrogen Receptor Cistrome in Mouse Liver Upon Acute E2 Treatment

Transcriptional regulation by the estrogen receptor-α (ER) has been investigated mainly in breast cancer cell lines, but estrogens such as 17β-estradiol (E2) exert numerous extrareproductive effects, particularly in the liver, where E2 exhibits both protective metabolic and deleterious thrombotic actions. To analyze the direct and early transcriptional effects of estrogens in the liver, we determined the E2-sensitive transcriptome and ER cistrome in mice after acute administration of E2 or placebo. These analyses revealed the early induction of genes involved in lipid metabolism, which fits with the crucial role of ER in the prevention of liver steatosis. Characterization of the chromatin state of ER binding sites (BSs) in mice expressing or not ER demonstrated that ER is not required per se for the establishment and/or maintenance of chromatin modifications at the majority of its BSs. This is presumably a consequence of a strong overlap between ER and hepatocyte nuclear factor 4α BSs. In contrast, 40% of the BSs of the pioneer factor forkhead box protein a (Foxa2) were dependent upon ER expression, and ER expression also affected the distribution of nucleosomes harboring dimethylated lysine 4 of Histone H3 around Foxa2 BSs. We finally show that, in addition to a network of liver-specific transcription factors including CCAAT/enhancer-binding protein and hepatocyte nuclear factor 4α, ER might be required for proper Foxa2 function in this tissue.

Sirt1 in cerebral ischemia

Cerebral ischemia is among the leading causes of death worldwide. It is characterized by a lack of blood flow to the brain that results in cell death and damage, ultimately causing motor, sensory, and cognitive impairments. Today, clinical treatment of cerebral ischemia, mostly stroke and cardiac arrest, is limited and new neuroprotective therapies are desperately needed. The Sirtuin family of oxidized nicotinamide adenine dinucleotide (NAD⁺)-dependent deacylases has been shown to govern several processes within the central nervous system as well as to possess neuroprotective properties in a variety of pathological conditions such as Alzheimer's Disease, Parkinson's Disease, and Huntington's Disease, among others. Recently, Sirt1 in particular has been identified as a mediator of cerebral ischemia, with potential as a possible therapeutic target. To gather studies relevant to this topic, we used PubMed and previous reviews to locate, select, and resynthesize the lines of evidence presented here. In this review, we will first describe some functions of Sirt1 in the brain, mainly neurodevelopment, learning and memory, and metabolic regulation. Second, we will discuss the experimental evidence that has implicated Sirt1 as a key protein in the regulation of cerebral ischemia as well as a potential target for the induction of ischemic tolerance.

Resveratrol Preconditioning Induces a Novel Extended Window of Ischemic Tolerance in the Mouse Brain

BACKGROUND AND PURPOSE

Prophylactic treatments that afford neuroprotection against stroke may emerge from the field of preconditioning. Resveratrol mimics ischemic preconditioning, reducing ischemic brain injury when administered 2 days before global ischemia in rats. This protection is linked to silent information regulator 2 homologue 1 (Sirt1) and enhanced mitochondrial function possibly through its repression of uncoupling protein 2. Brain-derived neurotrophic factor (BDNF) is another neuroprotective protein associated with Sirt1. In this study, we sought to identify the conditions of resveratrol preconditioning (RPC) that most robustly induce neuroprotection against focal ischemia in mice.

METHODS

We tested 4 different RPC paradigms against a middle cerebral artery occlusion model of stroke. Infarct volume and neurological score were calculated 24 hours after middle cerebral artery occlusion. Sirt1-chromatin binding was evaluated by ChIP-qPCR. Percoll gradients were used to isolate synaptic fractions, and changes in protein expression were determined via Western blot analysis. BDNF concentration was measured using a BDNF-specific ELISA assay.

RESULTS

Although repetitive RPC induced neuroprotection from middle cerebral artery occlusion, strikingly one application of RPC 14 days before middle cerebral artery occlusion showed the most robust protection, reducing infarct volume by 33% and improving neurological score by 28%. Fourteen days after RPC, Sirt1 protein was increased 1.5-fold and differentially bound to the uncoupling protein 2 and BDNF promoter regions. Accordingly, synaptic uncoupling protein 2 level decreased by 23% and cortical BDNF concentration increased 26%.

CONCLUSIONS

RPC induces a novel extended window of ischemic tolerance in the brain that lasts for at least 14 days. Our data suggest that this tolerance may be mediated by Sirt1 through upregulation of BDNF and downregulation of uncoupling protein 2.

Control of relative timing and stoichiometry by a master regulator

Developmental processes in cells require a series of complex steps. Often only a single master regulator activates genes in these different steps. This poses several challenges: some targets need to be ordered temporally, while co-functional targets may need to be synchronized in both time and expression level. Here we study in single cells the dynamic activation patterns of early meiosis genes in budding yeast, targets of the meiosis master regulator Ime1. We quantify the individual roles of the promoter and protein levels in expression pattern control, as well as the roles of individual promoter elements. We find a consistent expression pattern difference between a non-cofunctional pair of genes, and a highly synchronized activation of a co-functional pair. We show that dynamic control leading to these patterns is distributed between promoter, gene and external regions. Through specific reciprocal changes to the promoters of pairs of genes, we show that different genes can use different promoter elements to reach near identical activation patterns.

A cohesin-OCT4 complex mediates Sox enhancers to prime an early embryonic lineage

Short- and long-scales intra- and inter-chromosomal interactions are linked to gene transcription, but the molecular events underlying these structures and how they affect cell fate decision during embryonic development are poorly understood. One of the first embryonic cell fate decisions (that is, mesendoderm determination) is driven by the POU factor OCT4, acting in concert with the high-mobility group genes Sox-2 and Sox-17. Here we report a chromatin-remodelling mechanism and enhancer function that mediate cell fate switching. OCT4 alters the higher-order chromatin structure at both Sox-2 and Sox-17 loci. OCT4 titrates out cohesin and switches the Sox-17 enhancer from a locked (within an inter-chromosomal Sox-2 enhancer/CCCTC-binding factor CTCF/cohesin loop) to an active (within an intra-chromosomal Sox-17 promoter/enhancer/cohesin loop) state. SALL4 concomitantly mobilizes the polycomb complexes at the Soxs loci. Thus, OCT4/SALL4-driven cohesin- and polycombs-mediated changes in higher-order chromatin structure mediate instruction of early cell fate in embryonic cells.

Prioritizing causal disease genes using unbiased genomic features

BACKGROUND

Cardiovascular disease (CVD) is the leading cause of death in the developed world. Human genetic studies, including genome-wide sequencing and SNP-array approaches, promise to reveal disease genes and mechanisms representing new therapeutic targets. In practice, however, identification of the actual genes contributing to disease pathogenesis has lagged behind identification of associated loci, thus limiting the clinical benefits.

RESULTS

To aid in localizing causal genes, we develop a machine learning approach, Objective Prioritization for Enhanced Novelty (OPEN), which quantitatively prioritizes gene-disease associations based on a diverse group of genomic features. This approach uses only unbiased predictive features and thus is not hampered by a preference towards previously well-characterized genes. We demonstrate success in identifying genetic determinants for CVD-related traits, including cholesterol levels, blood pressure, and conduction system and cardiomyopathy phenotypes. Using OPEN, we prioritize genes, including FLNC, for association with increased left ventricular diameter, which is a defining feature of a prevalent cardiovascular disorder, dilated cardiomyopathy or DCM. Using a zebrafish model, we experimentally validate FLNC and identify a novel FLNC splice-site mutation in a patient with severe DCM.

CONCLUSION

Our approach stands to assist interpretation of large-scale genetic studies without compromising their fundamentally unbiased nature.

SAMNetWeb: identifying condition-specific networks linking signaling and transcription

MOTIVATION

High-throughput datasets such as genetic screens, mRNA expression assays and global phospho-proteomic experiments are often difficult to interpret due to inherent noise in each experimental system. Computational tools have improved interpretation of these datasets by enabling the identification of biological processes and pathways that are most likely to explain the measured results. These tools are primarily designed to analyse data from a single experiment (e.g. drug treatment versus control), creating a need for computational algorithms that can handle heterogeneous datasets across multiple experimental conditions at once.

SUMMARY

We introduce SAMNetWeb, a web-based tool that enables functional enrichment analysis and visualization of high-throughput datasets. SAMNetWeb can analyse two distinct data types (e.g. mRNA expression and global proteomics) simultaneously across multiple experimental systems to identify pathways activated in these experiments and then visualize the pathways in a single interaction network. Through the use of a multi-commodity flow based algorithm that requires each experiment 'share' underlying protein interactions, SAMNetWeb can identify distinct and common pathways across experiments.

AVAILABILITY AND IMPLEMENTATION

SAMNetWeb is freely available at http://fraenkel.mit.edu/samnetweb.

SuRFing the genomics wave: an R package for prioritising SNPs by functionality

Identifying functional non-coding variants is one of the greatest unmet challenges in genetics. To help address this, we introduce an R package, SuRFR, which integrates functional annotation and prior biological knowledge to prioritise candidate functional variants. SuRFR is publicly available, modular, flexible, fast, and simple to use. We demonstrate that SuRFR performs with high sensitivity and specificity and provide a widely applicable and scalable benchmarking dataset for model training and validation.

Website: http://www.cgem.ed.ac.uk/resources/

A dynamic CTCF chromatin binding landscape promotes DNA hydroxymethylation and transcriptional induction of adipocyte differentiation

CCCTC-binding factor (CTCF) is a ubiquitously expressed multifunctional transcription factor characterized by chromatin binding patterns often described as largely invariant. In this context, how CTCF chromatin recruitment and functionalities are used to promote cell type-specific gene expression remains poorly defined. Here, we show that, in addition to constitutively bound CTCF binding sites (CTS), the CTCF cistrome comprises a large proportion of sites showing highly dynamic binding patterns during the course of adipogenesis. Interestingly, dynamic CTCF chromatin binding is positively linked with changes in expression of genes involved in biological functions defining the different stages of adipogenesis. Importantly, a subset of these dynamic CTS are gained at cell type-specific regulatory regions, in line with a requirement for CTCF in transcriptional induction of adipocyte differentiation. This relates to, at least in part, CTCF requirement for transcriptional activation of both the nuclear receptor peroxisome proliferator-activated receptor gamma (PPARG) and its target genes. Functionally, we show that CTCF interacts with TET methylcytosine dioxygenase (TET) enzymes and promotes adipogenic transcriptional enhancer DNA hydroxymethylation. Our study reveals a dynamic CTCF chromatin binding landscape required for epigenomic remodeling of enhancers and transcriptional activation driving cell differentiation.

Latent phenotypes pervade gene regulatory circuits

BACKGROUND

Latent phenotypes are non-adaptive byproducts of adaptive phenotypes. They exist in biological systems as different as promiscuous enzymes and genome-scale metabolic reaction networks, and can give rise to evolutionary adaptations and innovations. We know little about their prevalence in the gene expression phenotypes of regulatory circuits, important sources of evolutionary innovations.

RESULTS

Here, we study a space of more than sixteen million three-gene model regulatory circuits, where each circuit is represented by a genotype, and has one or more functions embodied in one or more gene expression phenotypes. We find that the majority of circuits with single functions have latent expression phenotypes. Moreover, the set of circuits with a given spectrum of functions has a repertoire of latent phenotypes that is much larger than that of any one circuit. Most of this latent repertoire can be easily accessed through a series of small genetic changes that preserve a circuit's main functions. Both circuits and gene expression phenotypes that are robust to genetic change are associated with a greater number of latent phenotypes.

CONCLUSIONS

Our observations suggest that latent phenotypes are pervasive in regulatory circuits, and may thus be an important source of evolutionary adaptations and innovations involving gene regulation.

Identifying regulatory mechanisms underlying tumorigenesis using locus expression signature analysis

Retroviral insertional mutagenesis is a powerful tool for identifying putative cancer genes in mice. To uncover the regulatory mechanisms by which common insertion loci affect downstream processes, we supplemented genotyping data with genome-wide mRNA expression profiling data for 97 tumors induced by retroviral insertional mutagenesis. We developed locus expression signature analysis, an algorithm to construct and interpret the differential gene expression signature associated with each common insertion locus. Comparing locus expression signatures to promoter affinity profiles allowed us to build a detailed map of transcription factors whose protein-level regulatory activity is modulated by a particular locus. We also predicted a large set of drugs that might mitigate the effect of the insertion on tumorigenesis. Taken together, our results demonstrate the potential of a locus-specific signature approach for identifying mammalian regulatory mechanisms in a cancer context.

Large-scale quality analysis of published ChIP-seq data

ChIP-seq has become the primary method for identifying in vivo protein-DNA interactions on a genome-wide scale, with nearly 800 publications involving the technique appearing in PubMed as of December 2012. Individually and in aggregate, these data are an important and information-rich resource. However, uncertainties about data quality confound their use by the wider research community. Recently, the Encyclopedia of DNA Elements (ENCODE) project developed and applied metrics to objectively measure ChIP-seq data quality. The ENCODE quality analysis was useful for flagging datasets for closer inspection, eliminating or replacing poor data, and for driving changes in experimental pipelines. There had been no similarly systematic quality analysis of the large and disparate body of published ChIP-seq profiles. Here, we report a uniform analysis of vertebrate transcription factor ChIP-seq datasets in the Gene Expression Omnibus (GEO) repository as of April 1, 2012. The majority (55%) of datasets scored as being highly successful, but a substantial minority (20%) were of apparently poor quality, and another ∼25% were of intermediate quality. We discuss how different uses of ChIP-seq data are affected by specific aspects of data quality, and we highlight exceptional instances for which the metric values should not be taken at face value. Unexpectedly, we discovered that a significant subset of control datasets (i.e., no immunoprecipitation and mock immunoprecipitation samples) display an enrichment structure similar to successful ChIP-seq data. This can, in turn, affect peak calling and data interpretation. Published datasets identified here as high-quality comprise a large group that users can draw on for large-scale integrated analysis. In the future, ChIP-seq quality assessment similar to that used here could guide experimentalists at early stages in a study, provide useful input in the publication process, and be used to stratify ChIP-seq data for different community-wide uses.

Peroxisome proliferator-activated receptor γ regulates genes involved in insulin/insulin-like growth factor signaling and lipid metabolism during adipogenesis through functionally distinct enhancer classes

The nuclear receptor peroxisome proliferator-activated receptor (PPAR) is a transcription factor whose expression is induced during adipogenesis and that is required for the acquisition and control of mature adipocyte functions. Indeed, PPAR induces the expression of genes involved in lipid synthesis and storage through enhancers activated during adipocyte differentiation. Here, we show that PPAR also binds to enhancers already active in preadipocytes as evidenced by an active chromatin state including lower DNA methylation levels despite higher CpG content. These constitutive enhancers are linked to genes involved in the insulin/insulin-like growth factor signaling pathway that are transcriptionally induced during adipogenesis but to a lower extent than lipid metabolism genes, because of stronger basal expression levels in preadipocytes. This is consistent with the sequential involvement of hormonal sensitivity and lipid handling during adipocyte maturation and correlates with the chromatin structure dynamics at constitutive and activated enhancers. Interestingly, constitutive enhancers are evolutionary conserved and can be activated in other tissues, in contrast to enhancers controlling lipid handling genes whose activation is more restricted to adipocytes. Thus, PPAR utilizes both broadly active and cell type-specific enhancers to modulate the dynamic range of activation of genes involved in the adipogenic process.

Assessing computational methods for transcription factor target gene identification based on ChIP-seq data

Chromatin immunoprecipitation coupled with deep sequencing (ChIP-seq) has great potential for elucidating transcriptional networks, by measuring genome-wide binding of transcription factors (TFs) at high resolution. Despite the precision of these experiments, identification of genes directly regulated by a TF (target genes) is not trivial. Numerous target gene scoring methods have been used in the past. However, their suitability for the task and their performance remain unclear, because a thorough comparative assessment of these methods is still lacking. Here we present a systematic evaluation of computational methods for defining TF targets based on ChIP-seq data. We validated predictions based on 68 ChIP-seq studies using a wide range of genomic expression data and functional information. We demonstrate that peak-to-gene assignment is the most crucial step for correct target gene prediction and propose a parameter-free method performing most consistently across the evaluation tests.

Transcription factors (TFs) are the main regulators of gene transcription. Thus, knowing the genes that are targeted by a specific TF is of utmost importance for understanding developmental processes, cellular stress response, or disease etiology. Chromatin immunoprecipitation coupled with deep sequencing (ChIP-seq) allows for measuring the genome-wide binding of TFs. Several computational methods have been used for inferring the genes that are targeted by TFs using this binding information, but a thorough evaluation of their performance has not been performed so far. Here we present an assessment of a range of TF-target-calling methods using 68 ChIP-seq datasets. It turns out that the first step of the scoring, the assignment of binding events to genes, is the most important for correctly calling target genes. Our evaluation revealed important performance differences between the target-calling methods, with some simplistic methods exhibiting a particularly poor performance compared to more elaborate scorings. One of the methods is particularly attractive, because it does not require the a priori definition of any parameter — all parameters are ‘learned’ from the data. This and other methods tested were implemented in a freely available software package for future testing and application to other ChIP-seq datasets.

Models of signalling networks - what cell biologists can gain from them and give to them

Computational models of cell signalling are perceived by many biologists to be prohibitively complicated. Why do math when you can simply do another experiment? Here, we explain how conceptual models, which have been formulated mathematically, have provided insights that directly advance experimental cell biology. In the past several years, models have influenced the way we talk about signalling networks, how we monitor them, and what we conclude when we perturb them. These insights required wet-lab experiments but would not have arisen without explicit computational modelling and quantitative analysis. Today, the best modellers are cross-trained investigators in experimental biology who work closely with collaborators but also undertake experimental work in their own laboratories. Biologists would benefit by becoming conversant in core principles of modelling in order to identify when a computational model could be a useful complement to their experiments. Although the mathematical foundations of a model are useful to appreciate its strengths and weaknesses, they are not required to test or generate a worthwhile biological hypothesis computationally.

Analysis of in vitro insulin-resistance models and their physiological relevance to in vivo diet-induced adipose insulin resistance

Diet-induced obesity (DIO) predisposes individuals to insulin resistance, and adipose tissue has a major role in the disease. Insulin resistance can be induced in cultured adipocytes by a variety of treatments, but what aspects of the in vivo responses are captured by these models remains unknown. We use global RNA sequencing to investigate changes induced by TNF-α, hypoxia, dexamethasone, high insulin, and a combination of TNF-α and hypoxia, comparing the results to the changes in white adipose tissue from DIO mice. We found that different in vitro models capture distinct features of DIO adipose insulin resistance, and a combined treatment of TNF-α and hypoxia is most able to mimic the in vivo changes. Using genome-wide DNase I hypersensitivity followed by sequencing, we further examined the transcriptional regulation of TNF-α-induced insulin resistance, and we found that C/EPBβ is a potential key regulator of adipose insulin resistance.

Mapping genome-wide transcription factor binding sites in frozen tissues

BACKGROUND

Genome-wide maps of transcription factor binding sites in primary tissues can expand our understanding of genome function, transcriptional regulation, and genetic alterations that contribute to disease risk. However, almost all genome-wide studies of transcription factors have been in cell lines, and performing these experiments in tissues has been technically challenging and limited in throughput.

RESULTS

Here we outline a simple strategy for mapping transcription factor binding sites in frozen tissues that utilizes dry pulverization of samples and is scalable for high-throughput analyses. We show that the method leads to accurate and reproducible chromatin immunoprecipitation next-generation sequencing (ChIP-seq) data, and is highly sensitive, identifying high-quality transcription factor binding sites from chromatin corresponding to only 5 mg of liver tissue.

CONCLUSIONS

The enhanced reproducibility, robustness, and sensitivity of the dry pulverization method, in addition to the ease of implementation and scalability, makes ChIP-seq in primary tissues a widely accessible assay.

Roles of the developmental regulator unc-62/Homothorax in limiting longevity in Caenorhabditis elegans

The normal aging process is associated with stereotyped changes in gene expression, but the regulators responsible for these age-dependent changes are poorly understood. Using a novel genomics approach, we identified HOX co-factor unc-62 (Homothorax) as a developmental regulator that binds proximal to age-regulated genes and modulates lifespan. Although unc-62 is expressed in diverse tissues, its functions in the intestine play a particularly important role in modulating lifespan, as intestine-specific knockdown of unc-62 by RNAi increases lifespan. An alternatively-spliced, tissue-specific isoform of unc-62 is expressed exclusively in the intestine and declines with age. Through analysis of the downstream consequences of unc-62 knockdown, we identify multiple effects linked to aging. First, unc-62 RNAi decreases the expression of yolk proteins (vitellogenins) that aggregate in the body cavity in old age. Second, unc-62 RNAi results in a broad increase in expression of intestinal genes that typically decrease expression with age, suggesting that unc-62 activity balances intestinal resource allocation between yolk protein expression and fertility on the one hand and somatic functions on the other. Finally, in old age, the intestine shows increased expression of several aberrant genes; these UNC-62 targets are expressed predominantly in neuronal cells in developing animals, but surprisingly show increased expression in the intestine of old animals. Intestinal expression of some of these genes during aging is detrimental for longevity; notably, increased expression of insulin ins-7 limits lifespan by repressing activity of insulin pathway response factor DAF-16/FOXO in aged animals. These results illustrate how unc-62 regulation of intestinal gene expression is responsible for limiting lifespan during the normal aging process.

Long noncoding RNAs regulate adipogenesis

The prevalence of obesity has led to a surge of interest in understanding the detailed mechanisms underlying adipocyte development. Many protein-coding genes, mRNAs, and microRNAs have been implicated in adipocyte development, but the global expression patterns and functional contributions of long noncoding RNA (lncRNA) during adipogenesis have not been explored. Here we profiled the transcriptome of primary brown and white adipocytes, preadipocytes, and cultured adipocytes and identified 175 lncRNAs that are specifically regulated during adipogenesis. Many lncRNAs are adipose-enriched, strongly induced during adipogenesis, and bound at their promoters by key transcription factors such as peroxisome proliferator-activated receptor γ (PPARγ) and CCAAT/enhancer-binding protein α (CEBPα). RNAi-mediated loss of function screens identified functional lncRNAs with varying impact on adipogenesis. Collectively, we have identified numerous lncRNAs that are functionally required for proper adipogenesis.

Extensive changes in DNA methylation are associated with expression of mutant huntingtin

The earliest stages of Huntington disease are marked by changes in gene expression that are caused in an indirect and poorly understood manner by polyglutamine expansions in the huntingtin (HTT) protein. To explore the hypothesis that DNA methylation may be altered in cells expressing mutated HTT, we use reduced representation bisulfite sequencing (RRBS) to map sites of DNA methylation in cells carrying either wild-type or mutant HTT. We find that a large fraction of the genes that change in expression in the presence of mutant huntingtin demonstrate significant changes in DNA methylation. Regions with low CpG content, which have previously been shown to undergo methylation changes in response to neuronal activity, are disproportionately affected. On the basis of the sequence of regions that change in methylation, we identify AP-1 and SOX2 as transcriptional regulators associated with DNA methylation changes, and we confirm these hypotheses using genome-wide chromatin immunoprecipitation sequencing (ChIP-Seq). Our findings suggest new mechanisms for the effects of polyglutamine-expanded HTT. These results also raise important questions about the potential effects of changes in DNA methylation on neurogenesis and cognitive decline in patients with Huntington disease.

Comprehensive meta-analysis of Signal Transducers and Activators of Transcription (STAT) genomic binding patterns discerns cell-specific cis-regulatory modules

BACKGROUND

Cytokine-activated transcription factors from the STAT (Signal Transducers and Activators of Transcription) family control common and context-specific genetic programs. It is not clear to what extent cell-specific features determine the binding capacity of seven STAT members and to what degree they share genetic targets. Molecular insight into the biology of STATs was gained from a meta-analysis of 29 available ChIP-seq data sets covering genome-wide occupancy of STATs 1, 3, 4, 5A, 5B and 6 in several cell types.

RESULTS

We determined that the genomic binding capacity of STATs is primarily defined by the cell type and to a lesser extent by individual family members. For example, the overlap of shared binding sites between STATs 3 and 5 in T cells is greater than that between STAT5 in T cells and non-T cells. Even for the top 1,000 highly enriched STAT binding sites, ~15% of STAT5 binding sites in mouse female liver are shared by other STATs in different cell types while in T cells ~90% of STAT5 binding sites are co-occupied by STAT3, STAT4 and STAT6. In addition, we identified 116 cis-regulatory modules (CRM), which are recognized by all STAT members across cell types defining a common JAK-STAT signature. Lastly, in liver STAT5 binding significantly coincides with binding of the cell-specific transcription factors HNF4A, FOXA1 and FOXA2 and is associated with cell-type specific gene transcription.

CONCLUSIONS

Our results suggest that genomic binding of STATs is primarily determined by the cell type and further specificity is achieved in part by juxtaposed binding of cell-specific transcription factors.

Sequence signatures extracted from proximal promoters can be used to predict distal enhancers

BACKGROUND

Gene expression is controlled by proximal promoters and distal regulatory elements such as enhancers. While the activity of some promoters can be invariant across tissues, enhancers tend to be highly tissue-specific.

RESULTS

We compiled sets of tissue-specific promoters based on gene expression profiles of 79 human tissues and cell types. Putative transcription factor binding sites within each set of sequences were used to train a support vector machine classifier capable of distinguishing tissue-specific promoters from control sequences. We obtained reliable classifiers for 92% of the tissues, with an area under the receiver operating characteristic curve between 60% (for subthalamic nucleus promoters) and 98% (for heart promoters). We next used these classifiers to identify tissue-specific enhancers, scanning distal non-coding sequences in the loci of the 200 most highly and lowly expressed genes. Thirty percent of reliable classifiers produced consistent enhancer predictions, with significantly higher densities in the loci of the most highly expressed compared to lowly expressed genes. Liver enhancer predictions were assessed in vivo using the hydrodynamic tail vein injection assay. Fifty-eight percent of the predictions yielded significant enhancer activity in the mouse liver, whereas a control set of five sequences was completely negative.

CONCLUSIONS

We conclude that promoters of tissue-specific genes often contain unambiguous tissue-specific signatures that can be learned and used for the de novo prediction of enhancers.

Sequential activation of genetic programs in mouse mammary epithelium during pregnancy depends on STAT5A/B concentration

The transcription factors Signal Transducer and Activator of Transcription (STAT) 5A/B mediate prolactin-induced mammary development during pregnancy. However, it is not clear how the different processes, expansion and maturation of alveolar precursor cells and the differential induction of milk protein genes are regulated on a molecular level. We have used mouse genetics and genome-wide analyses to determine how altering concentrations of STAT5A and STAT5B impacts mammary epithelial development during pregnancy and the regulation of target genes. The presence of only a single Stat5a or Stat5b allele was sufficient for the establishment of histologically undifferentiated alveolar units and two alleles permitted the execution of a differentiation program similar to that found with all four alleles. While one copy of Stat5 induced limited expression of target genes, two copies activated a lactation-like gene signature. Using ChIP-seq analyses on intact tissue under physiological conditions, we found that highly expressed and regulated genes were bound by STAT5 in their promoter proximal regions, whereas upstream binding had minor biological consequences. Remarkably, 80% of the genes bound by STAT5 in vivo were not under STAT5 control. RNA polymerase II intensity was directly proportional to STAT5 concentration only on STAT5 regulated genes providing mechanistic insight by which STAT5 activates mammary specific genes.

ChIPBase: a database for decoding the transcriptional regulation of long non-coding RNA and microRNA genes from ChIP-Seq data

Long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) represent two classes of important non-coding RNAs in eukaryotes. Although these non-coding RNAs have been implicated in organismal development and in various human diseases, surprisingly little is known about their transcriptional regulation. Recent advances in chromatin immunoprecipitation with next-generation DNA sequencing (ChIP-Seq) have provided methods of detecting transcription factor binding sites (TFBSs) with unprecedented sensitivity. In this study, we describe ChIPBase (http://deepbase.sysu.edu.cn/chipbase/), a novel database that we have developed to facilitate the comprehensive annotation and discovery of transcription factor binding maps and transcriptional regulatory relationships of lncRNAs and miRNAs from ChIP-Seq data. The current release of ChIPBase includes high-throughput sequencing data that were generated by 543 ChIP-Seq experiments in diverse tissues and cell lines from six organisms. By analysing millions of TFBSs, we identified tens of thousands of TF-lncRNA and TF-miRNA regulatory relationships. Furthermore, two web-based servers were developed to annotate and discover transcriptional regulatory relationships of lncRNAs and miRNAs from ChIP-Seq data. In addition, we developed two genome browsers, deepView and genomeView, to provide integrated views of multidimensional data. Moreover, our web implementation supports diverse query types and the exploration of TFs, lncRNAs, miRNAs, gene ontologies and pathways.

Spatiotemporal clustering of the epigenome reveals rules of dynamic gene regulation

Spatial organization of different epigenomic marks was used to infer functions of the epigenome. It remains unclear what can be learned from the temporal changes of the epigenome. Here, we developed a probabilistic model to cluster genomic sequences based on the similarity of temporal changes of multiple epigenomic marks during a cellular differentiation process. We differentiated mouse embryonic stem (ES) cells into mesendoderm cells. At three time points during this differentiation process, we used high-throughput sequencing to measure seven histone modifications and variants—H3K4me1/2/3, H3K27ac, H3K27me3, H3K36me3, and H2A.Z; two DNA modifications—5-mC and 5-hmC; and transcribed mRNAs and noncoding RNAs (ncRNAs). Genomic sequences were clustered based on the spatiotemporal epigenomic information. These clusters not only clearly distinguished gene bodies, promoters, and enhancers, but also were predictive of bidirectional promoters, miRNA promoters, and piRNAs. This suggests specific epigenomic patterns exist on piRNA genes much earlier than germ cell development. Temporal changes of H3K4me2, unmethylated CpG, and H2A.Z were predictive of 5-hmC changes, suggesting unmethylated CpG and H3K4me2 as potential upstream signals guiding TETs to specific sequences. Several rules on combinatorial epigenomic changes and their effects on mRNA expression and ncRNA expression were derived, including a simple rule governing the relationship between 5-hmC and gene expression levels. A Sox17 enhancer containing a FOXA2 binding site and a Foxa2 enhancer containing a SOX17 binding site were identified, suggesting a positive feedback loop between the two mesendoderm transcription factors. These data illustrate the power of using epigenome dynamics to investigate regulatory functions.