Statistical significance of cis-regulatory modules

SETDB1 regulates short interspersed nuclear elements and chromatin loop organization in mouse neural precursor cells

BACKGROUND

Transposable elements play a critical role in maintaining genome architecture during neurodevelopment. Short Interspersed Nuclear Elements (SINEs), a major subtype of transposable elements, are known to harbor binding sites for the CCCTC-binding factor (CTCF) and pivotal in orchestrating chromatin organization. However, the regulatory mechanisms controlling the activity of SINEs in the developing brain remains elusive.

RESULTS

In our study, we conduct a comprehensive genome-wide epigenetic analysis in mouse neural precursor cells using ATAC-seq, ChIP-seq, whole genome bisulfite sequencing, in situ Hi-C, and RNA-seq. Our findings reveal that the SET domain bifurcated histone lysine methyltransferase 1 (SETDB1)-mediated H3K9me3, in conjunction with DNA methylation, restricts chromatin accessibility on a selective subset of SINEs in neural precursor cells. Mechanistically, loss of Setdb1 increases CTCF access to these SINE elements and contributes to chromatin loop reorganization. Moreover, de novo loop formation contributes to differential gene expression, including the dysregulation of genes enriched in mitotic pathways. This leads to the disruptions of cell proliferation in the embryonic brain after genetic ablation of Setdb1 both in vitro and in vivo.

CONCLUSIONS

In summary, our study sheds light on the epigenetic regulation of SINEs in mouse neural precursor cells, suggesting their role in maintaining chromatin organization and cell proliferation during neurodevelopment.

Chromosomal-level reference genome of a wild North American mallard (Anas platyrhynchos)

The mallard (Anas platyrhynchos) is one of the most common, economically, and socially important birds around the world. Mallards were not only an important food source for early humans but eventually becoming intimately linked with people as they were domesticated over the last 2,000 years. To date, mallard genomes are largely reconstructed from samples of domestic or unknown genetic heritage. Here, we report the first high-quality genome assembly and annotation of a genetically vetted wild mallard from North America (NAwild_v1.0). The genome was assembled using a combination of shotgun libraries, proximity ligation Chicago, and Dovetail Hi-C libraries. The final assembly is ∼1.04 Gb in size, with 98.3% of the sequence located in 30 full or nearly full chromosome-level scaffolds, and with a N50/L50 of 79.1 Mb/4 scaffolds. We used a combination of gene prediction and similarity approaches to annotate a total of 23,584 functional genes, of which 19,242 were associated to GO terms. The genome assembly and the set of annotated genes yielded a 95.4% completeness score when compared with the BUSCO aves_odb10 dataset. Next, we aligned 3 previously published mallard genomes to ours, and demonstrate how runs of homozygosity and nucleotide diversity are substantially higher and lower, respectively, to ours and how these artificially changed genomes resulted in profoundly different and biased demographic histories. Our wild mallard assembly not only provides a valuable resource to shed light onto genome evolution, speciation, and other adaptive processes, but also helping with identifying functional genes that have been significantly altered during the domestication process.

Prediction of CTCF loop anchor based on machine learning

Introduction: Various activities in biological cells are affected by three-dimensional genome structure. The insulators play an important role in the organization of higher-order structure. CTCF is a representative of mammalian insulators, which can produce barriers to prevent the continuous extrusion of chromatin loop. As a multifunctional protein, CTCF has tens of thousands of binding sites in the genome, but only a portion of them can be used as anchors of chromatin loops. It is still unclear how cells select the anchor in the process of chromatin looping.

Methods: In this paper, a comparative analysis is performed to investigate the sequence preference and binding strength of anchor and non-anchor CTCF binding sites. Furthermore, a machine learning model based on the CTCF binding intensity and DNA sequence is proposed to predict which CTCF sites can form chromatin loop anchors.

Results: The accuracy of the machine learning model that we constructed for predicting the anchor of the chromatin loop mediated by CTCF reached 0.8646. And we find that the formation of loop anchor is mainly influenced by the CTCF binding strength and binding pattern (which can be interpreted as the binding of different zinc fingers).

Discussion: In conclusion, our results suggest that The CTCF core motif and it’s flanking sequence may be responsible for the binding specificity. This work contributes to understanding the mechanism of loop anchor selection and provides a reference for the prediction of CTCF-mediated chromatin loops.

Interplay between the Chd4/NuRD Complex and the Transcription Factor Znf219 Control Cardiac Cell Identity

The sarcomere regulates striated muscle contraction. This structure is composed of several myofibril proteins, isoforms of which are encoded by genes specific to either the heart or skeletal muscle. The chromatin remodeler complex Chd4/NuRD regulates the transcriptional expression of these specific sarcomeric programs by repressing genes of the skeletal muscle sarcomere in the heart. Aberrant expression of skeletal muscle genes induced by the loss of Chd4 in the heart leads to sudden death due to defects in cardiomyocyte contraction that progress to arrhythmia and fibrosis. Identifying the transcription factors (TFs) that recruit Chd4/NuRD to repress skeletal muscle genes in the myocardium will provide important information for understanding numerous cardiac pathologies and, ultimately, pinpointing new therapeutic targets for arrhythmias and cardiomyopathies. Here, we sought to find Chd4 interactors and their function in cardiac homeostasis. We therefore describe a physical interaction between Chd4 and the TF Znf219 in cardiac tissue. Znf219 represses the skeletal-muscle sarcomeric program in cardiomyocytes in vitro and in vivo, similarly to Chd4. Aberrant expression of skeletal-muscle sarcomere proteins in mouse hearts with knocked down Znf219 translates into arrhythmias, accompanied by an increase in PR interval. These data strongly suggest that the physical and genetic interaction of Znf219 and Chd4 in the mammalian heart regulates cardiomyocyte identity and myocardial contraction.

Single-cell transcriptional changes associated with drug tolerance and response to combination therapies in cancer

Tyrosine kinase inhibitors were found to be clinically effective for treatment of patients with certain subsets of cancers carrying somatic mutations in receptor tyrosine kinases. However, the duration of clinical response is often limited, and patients ultimately develop drug resistance. Here, we use single-cell RNA sequencing to demonstrate the existence of multiple cancer cell subpopulations within cell lines, xenograft tumors and patient tumors. These subpopulations exhibit epigenetic changes and differential therapeutic sensitivity. Recurrently overrepresented ontologies in genes that are differentially expressed between drug tolerant cell populations and drug sensitive cells include epithelial-to-mesenchymal transition, epithelium development, vesicle mediated transport, drug metabolism and cholesterol homeostasis. We show analysis of identified markers using the LINCS database to predict and functionally validate small molecules that target selected drug tolerant cell populations. In combination with EGFR inhibitors, crizotinib inhibits the emergence of a defined subset of EGFR inhibitor-tolerant clones. In this study, we describe the spectrum of changes associated with drug tolerance and inhibition of specific tolerant cell subpopulations with combination agents.

Loop competition and extrusion model predicts CTCF interaction specificity

Three-dimensional chromatin looping interactions play an important role in constraining enhancer–promoter interactions and mediating transcriptional gene regulation. CTCF is thought to play a critical role in the formation of these loops, but the specificity of which CTCF binding events form loops and which do not is difficult to predict. Loops often have convergent CTCF binding site motif orientation, but this constraint alone is only weakly predictive of genome-wide interaction data. Here we present an easily interpretable and simple mathematical model of CTCF mediated loop formation which is consistent with Cohesin extrusion and can predict ChIA-PET CTCF looping interaction measurements with high accuracy. Competition between overlapping loops is a critical determinant of loop specificity. We show that this model is consistent with observed chromatin interaction frequency changes induced by CTCF binding site deletion, inversion, and mutation, and is also consistent with observed constraints on validated enhancer–promoter interactions.

Boundaries of topologically associated domains in genomes are marked by CTCF and cohesin binding. Here the authors predict CTCF interaction specificity by building a simple mathematical model with features including loop competition and extrusion.

Implication of a new function of human tDNAs in chromatin organization

Transfer RNA genes (tDNAs) are essential genes that encode tRNAs in all species. To understand new functions of tDNAs, other than that of encoding tRNAs, we used ENCODE data to examine binding characteristics of transcription factors (TFs) for all tDNA regions (489 loci) in the human genome. We divided the tDNAs into three groups based on the number of TFs that bound to them. At the two extremes were tDNAs to which many TFs bound (Group 1) and those to which no TFs bound (Group 3). Several TFs involved in chromatin remodeling such as ATF3, EP300 and TBL1XR1 bound to almost all Group 1 tDNAs. Furthermore, almost all Group 1 tDNAs included DNase I hypersensitivity sites and may thus interact with other chromatin regions through their bound TFs, and they showed highly conserved synteny across tetrapods. In contrast, Group 3 tDNAs did not possess these characteristics. These data suggest the presence of a previously uncharacterized function of these tDNAs. We also examined binding of CTCF to tDNAs and their involvement in topologically associating domains (TADs) and lamina-associated domains (LADs), which suggest a new perspective on the evolution and function of tDNAs.

Rbf Activates the Myogenic Transcriptional Program to Promote Skeletal Muscle Differentiation

The importance of the retinoblastoma tumor suppressor protein pRB in cell cycle control is well established. However, less is known about its role in differentiation during animal development. Here, we investigated the role of Rbf, the Drosophila pRB homolog, in adult skeletal muscles. We found that the depletion of Rbf severely reduced muscle growth and altered myofibrillogenesis but only minimally affected myoblast proliferation. We identified an Rbf-dependent transcriptional program in late muscle development that is distinct from the canonical role of Rbf in cell cycle control. Unexpectedly, Rbf acts as a transcriptional activator of the myogenic and metabolic genes in the growing muscles. The genomic regions bound by Rbf contained the binding sites of several factors that genetically interacted with Rbf by modulating Rbf-dependent phenotype. Thus, our results reveal a distinctive role for Rbf as a direct activator of the myogenic transcriptional program that drives late muscle differentiation.

Inactivation of the tumor suppressor RB, an obligatory step in most cancers, results in unrestrained cell cycle progression. Zappia et al. show that Rbf, the RB Drosophila ortholog, directly activates the metabolic program that accompanies muscle development. This work expands the understanding of the plethora of Rbf functions.

Peroxisome proliferator-activated receptor gamma controls prostate cancer cell growth through AR-dependent and independent mechanisms

BACKGROUND

Prostate cancer (PC) remains a leading cause of cancer mortality and the most successful chemopreventative and treatment strategies for PC come from targeting the androgen receptor (AR). Although AR plays a key role, it is likely that other molecular pathways also contribute to PC, making it essential to identify and develop drugs against novel targets. Recent studies have identified peroxisome proliferator-activated receptor gamma (PPARγ), a nuclear receptor that regulates fatty acid (FA) metabolism, as a novel target in PC, and suggest that inhibitors of PPARγ could be used to treat existing disease. We hypothesized that PPARγ acts through AR-dependent and independent mechanisms to control PC development and growth and that PPARγ inhibition is a viable PC treatment strategy.

METHODS

Immunohistochemistry was used to determine expression of PPARү in a cohort of patients with PC. Standard molecular techniques were used to investigate the PPARү signaling in PC cells as well a xenograft mouse model to test PPARү inhibition in vivo. Kaplan-Meier curves were created using cBioportal.

RESULTS

We confirmed the expression of PPARү in human PC. We then showed that small molecule inhibition of PPARγ decreases the growth of AR-positive and -negative PC cells in vitro and that T0070907, a potent PPARγ antagonist, significantly decreased the growth of human PC xenografts in nude mice. We found that PPARγ antagonists or small interfering RNA (siRNA) do not affect mitochondrial activity nor do they cause apoptosis; instead, they arrest the cell cycle. In AR-positive PC cells, antagonists and siRNAs reduce AR transcript and protein levels, which could contribute to growth inhibition. AR-independent effects on growth appear to be mediated by effects on FA metabolism as the specific FASN inhibitor, Fasnall, inhibited PC cell growth but did not have an additive effect when combined with PPARγ antagonists. Patients with increased PPARү target gene expression, but not alterations in PPARү itself, were found to have significantly worse overall survival.

CONCLUSIONS

Having elucidated the direct cancer cell effects of PPARγ inhibition, our studies have helped to determine the role of PPARγ in PC growth, and support the hypothesis that PPARγ inhibition is an effective strategy for PC treatment.

Mitigation of off-target toxicity in CRISPR-Cas9 screens for essential non-coding elements

Pooled CRISPR-Cas9 screens are a powerful method for functionally characterizing regulatory elements in the non-coding genome, but off-target effects in these experiments have not been systematically evaluated. Here, we investigate Cas9, dCas9, and CRISPRi/a off-target activity in screens for essential regulatory elements. The sgRNAs with the largest effects in genome-scale screens for essential CTCF loop anchors in K562 cells were not single guide RNAs (sgRNAs) that disrupted gene expression near the on-target CTCF anchor. Rather, these sgRNAs had high off-target activity that, while only weakly correlated with absolute off-target site number, could be predicted by the recently developed GuideScan specificity score. Screens conducted in parallel with CRISPRi/a, which do not induce double-stranded DNA breaks, revealed that a distinct set of off-targets also cause strong confounding fitness effects with these epigenome-editing tools. Promisingly, filtering of CRISPRi libraries using GuideScan specificity scores removed these confounded sgRNAs and enabled identification of essential regulatory elements.

Spatial chromatin architecture alteration by structural variations in human genomes at the population scale

BACKGROUND

The number of reported examples of chromatin architecture alterations involved in the regulation of gene transcription and in disease is increasing. However, no genome-wide testing has been performed to assess the abundance of these events and their importance relative to other factors affecting genome regulation. This is particularly interesting given that a vast majority of genetic variations identified in association studies are located outside coding sequences. This study attempts to address this lack by analyzing the impact on chromatin spatial organization of genetic variants identified in individuals from 26 human populations and in genome-wide association studies.

RESULTS

We assess the tendency of structural variants to accumulate in spatially interacting genomic segments and design an algorithm to model chromatin conformational changes caused by structural variations. We show that differential gene transcription is closely linked to the variation in chromatin interaction networks mediated by RNA polymerase II. We also demonstrate that CTCF-mediated interactions are well conserved across populations, but enriched with disease-associated SNPs. Moreover, we find boundaries of topological domains as relatively frequent targets of duplications, which suggest that these duplications can be an important evolutionary mechanism of genome spatial organization.

CONCLUSIONS

This study assesses the critical impact of genetic variants on the higher-order organization of chromatin folding and provides insight into the mechanisms regulating gene transcription at the population scale, of which local arrangement of chromatin loops seems to be the most significant. It provides the first insight into the variability of the human 3D genome at the population scale.

Machine learning polymer models of three-dimensional chromatin organization in human lymphoblastoid cells

We present machine learning models of human genome three-dimensional structure that combine one dimensional (linear) sequence specificity, epigenomic information, and transcription factor binding profiles, with the polymer-based biophysical simulations in order to explain the extensive long-range chromatin looping observed in ChIA-PET experiments for lymphoblastoid cells. Random Forest, Gradient Boosting Machine (GBM), and Deep Learning models were constructed and evaluated, when predicting high-resolution interactions within Topologically Associating Domains (TADs). The predicted interactions are consistent with the experimental long-read ChIA-PET interactions mediated by CTCF and RNAPOL2 for GM12878 cell line. The contribution of sequence information and chromatin state defined by epigenomic features to the prediction task is analyzed and reported, when using them separately and combined. Furthermore, we design three-dimensional models of chromatin contact domains (CCDs) using real (ChIA-PET) and predicted looping interactions. Initial results show a similarity between both types of 3D computational models (constructed from experimental or predicted interactions). This observation confirms the association between genome sequence, epigenomic and transcription factor profiles, and three-dimensional interactions.

Discovery of Allele-Specific Protein-RNA Interactions in Human Transcriptomes

Gene expression is tightly regulated at the post-transcriptional level through splicing, transport, translation, and decay. RNA-binding proteins (RBPs) play key roles in post-transcriptional gene regulation, and genetic variants that alter RBP-RNA interactions can affect gene products and functions. We developed a computational method ASPRIN (Allele-Specific Protein-RNA Interaction) that uses a joint analysis of CLIP-seq (cross-linking and immunoprecipitation followed by high-throughput sequencing) and RNA-seq data to identify genetic variants that alter RBP-RNA interactions by directly observing the allelic preference of RBP from CLIP-seq experiments as compared to RNA-seq. We used ASPRIN to systematically analyze CLIP-seq and RNA-seq data for 166 RBPs in two ENCODE (Encyclopedia of DNA Elements) cell lines. ASPRIN identified genetic variants that alter RBP-RNA interactions by modifying RBP binding motifs within RNA. Moreover, through an integrative ASPRIN analysis with population-scale RNA-seq data, we showed that ASPRIN can help reveal potential causal variants that affect alternative splicing via allele-specific protein-RNA interactions.

N6-Methyladenine DNA Methylation in Japonica and Indica Rice Genomes and Its Association with Gene Expression, Plant Development, and Stress Responses

N⁶-Methyladenine (6mA) DNA methylation has recently been implicated as a potential new epigenetic marker in eukaryotes, including the dicot model Arabidopsis thaliana. However, the conservation and divergence of 6mA distribution patterns and functions in plants remain elusive. Here we report high-quality 6mA methylomes at single-nucleotide resolution in rice based on substantially improved genome sequences of two rice cultivars, Nipponbare (Nip; Japonica) and 93-11 (Indica). Analysis of 6mA genomic distribution and its association with transcription suggest that 6mA distribution and function is rather conserved between rice and Arabidopsis. We found that 6mA levels are positively correlated with the expression of key stress-related genes, which may be responsible for the difference in stress tolerance between Nip and 93-11. Moreover, we showed that mutations in DDM1 cause defects in plant growth and decreased 6mA level. Our results reveal that 6mA is a conserved DNA modification that is positively associated with gene expression and contributes to key agronomic traits in plants.

Polymer Simulations of Heteromorphic Chromatin Predict the 3D Folding of Complex Genomic Loci

Chromatin folded into 3D macromolecular structures is often analyzed by chromosome conformation capture (3C) and fluorescence in situ hybridization (FISH) techniques, but these frequently provide contradictory results. Chromatin can be modeled as a simple polymer composed of a connected chain of units. By embedding data for epigenetic marks (H3K27ac), chromatin accessibility (assay for transposase-accessible chromatin using sequencing [ATAC-seq]), and structural anchors (CCCTC-binding factor [CTCF]), we developed a highly predictive heteromorphic polymer (HiP-HoP) model, where the chromatin fiber varied along its length; combined with diffusing protein bridges and loop extrusion, this model predicted the 3D organization of genomic loci at a population and single-cell level. The model was validated at several gene loci, including the complex Pax6 gene, and was able to determine locus conformations across cell types with varying levels of transcriptional activity and explain different mechanisms of enhancer use. Minimal a priori knowledge of epigenetic marks is sufficient to recapitulate complex genomic loci in 3D and enable predictions of chromatin folding paths.

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HiP-HoP: highly predictive heteromorphic polymer model to analyze chromatin structure

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Polymer simulations use widely available epigenetic and protein binding data as input

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Validate HiP-HoP model at complex loci using 3D FISH and Capture-C

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Simulations uncover striking conformational variability in chromatin fiber folding

Fast sequence analysis based on diamond sampling

Both in DNA and protein contexts, an important method for modelling motifs is to utilize position weight matrix (PWM) in biological sequences. With the development of genome sequencing technology, the quantity of the sequence data is increasing explosively, so the faster searching algorithms which have the ability to meet the increasingly need are desired to develop. In this paper, we proposed a method for speeding up the searching process of candidate transcription factor binding sites (TFBS), and the users can be allowed to specify p threshold to get the desired trade-off between speed and sensitivity for a particular sequence analysis. Moreover, the proposed method can also be generalized to large-scale annotation and sequence projects.

The Bio-Analytic Resource for Plant Biology

Bioinformatic tools have become part of the way plant researchers undertake investigations. Large data sets encompassing genomes, transcriptomes, proteomes, epigenomes, and other "-omes" that have been generated in the past decade may be easily accessed with such tools, such that hypotheses may be generated at the click of a mouse. In this chapter, we'll cover the use of bioinformatic tools available at the Bio-Analytic Resource for Plant Biology at http://bar.utoronto.ca for exploring gene expression and coexpression patterns, undertaking promoter analyses, performing functional classification enrichment analyses for sets of genes, and examining protein-protein interactions. We also touch on some newer bioinformatic tools that allow integration of data from several sources for improved hypothesis generation, both for Arabidopsis and translationally. Most of the data sets come from Arabidopsis, but useful BAR tools for other species will be mentioned where appropriate.

ChIP-Seq analysis identifies p27(Kip1)-target genes involved in cell adhesion and cell signalling in mouse embryonic fibroblasts

The protein p27^Kip1 (p27), a member of the Cip-Kip family of cyclin-dependent kinase inhibitors, is involved in tumorigenesis and a correlation between reduced levels of this protein in human tumours and a worse prognosis has been established. Recent reports revealed that p27 also behaves as a transcriptional regulator. Thus, it has been postulated that the development of tumours with low amounts of p27 could be propitiated by deregulation of transcriptional programs under the control of p27. However, these programs still remain mostly unknown. The aim of this study has been to define the transcriptional programs regulated by p27 by first identifying the p27-binding sites (p27-BSs) on the whole chromatin of quiescent mouse embryonic fibroblasts. The chromatin regions associated to p27 have been annotated to the most proximal genes and it has been considered that the expression of these genes could by regulated by p27. The identification of the chromatin p27-BSs has been performed by Chromatin Immunoprecipitation Sequencing (ChIP-seq). Results revealed that p27 associated with 1839 sites that were annotated to 1417 different genes being 852 of them protein coding genes. Interestingly, most of the p27-BSs were in distal intergenic regions and introns whereas, in contrast, its association with promoter regions was very low. Gene ontology analysis of the protein coding genes revealed a number of relevant transcriptional programs regulated by p27 as cell adhesion, intracellular signalling and neuron differentiation among others. We validated the interaction of p27 with different chromatin regions by ChIP followed by qPCR and demonstrated that the expressions of several genes belonging to these programs are actually regulated by p27. Finally, cell adhesion assays revealed that the adhesion of p27^-/- cells to the plates was much higher that controls, revealing a role of p27 in the regulation of a transcriptional program involved in cell adhesion.

p27Kip1, PCAF and PAX5 cooperate in the transcriptional regulation of specific target genes

The cyclin-dependent kinase inhibitor p27^Kip1 (p27) also behaves as a transcriptional repressor. Data showing that the p300/CBP-associated factor (PCAF) acetylates p27 inducing its degradation suggested that PCAF and p27 could collaborate in the regulation of transcription. However, this possibility remained to be explored. We analyzed here the transcriptional programs regulated by PCAF and p27 in the colon cancer cell line HCT116 by chromatin immunoprecipitation sequencing (ChIP-seq). We identified 269 protein-encoding genes that contain both p27 and PCAF binding sites being the majority of these sites different for PCAF and p27. PCAF or p27 knock down revealed that both regulate the expression of these genes, PCAF as an activator and p27 as a repressor. The double knock down of PCAF and p27 strongly reduced their expression indicating that the activating role of PCAF overrides the repressive effect of p27. We also observed that the transcription factor Pax5 interacts with both p27 and PCAF and that the knock down of Pax5 induces the expression of p27/PCAF target genes indicating that it also participates in the transcriptional regulation mediated by p27/PCAF. In summary, we report here a previously unknown mechanism of transcriptional regulation mediated by p27, Pax5 and PCAF.

Vertical sleeve gastrectomy reverses diet-induced gene-regulatory changes impacting lipid metabolism

Vertical sleeve gastrectomy (VSG) produces sustainable weight loss, remission of type 2 diabetes (T2D), and improvement of nonalcoholic fatty liver disease (NAFLD). However, the molecular mechanisms underlying the metabolic benefits of VSG have remained elusive. According to our previous results, diet-induced obesity induces epigenetic modifications to chromatin in mouse liver. We demonstrate here that VSG in C57BL/6J wild-type male mice can reverse these chromatin modifications and thereby impact the expression of key metabolic genes. Genes involved in lipid metabolism, especially omega-6 fatty acid metabolism, are up-regulated in livers of mice after VSG while genes in inflammatory pathways are down-regulated after VSG. Consistent with gene expression changes, regulatory regions near genes involved in inflammatory response displayed decreased chromatin accessibility after VSG. Our results indicate that VSG induces global regulatory changes that impact hepatic inflammatory and lipid metabolic pathways, providing new insight into the mechanisms underlying the beneficial metabolic effects induced by VSG.

Unliganded estrogen receptor alpha regulates vascular cell function and gene expression

The unliganded form of the estrogen receptor is generally thought to be inactive. Our prior studies, however, suggested that unliganded estrogen receptor alpha (ERα) exacerbates adverse vascular injury responses in mice. Here, we show that the presence of unliganded ERα decreases vascular endothelial cell (EC) migration and proliferation, increases smooth muscle cell (SMC) proliferation, and increases inflammatory responses in cultured ECs and SMCs. Unliganded ERα also regulates many genes in vascular ECs and mouse aorta. Activation of ERα by E2 reverses the cell physiological effects of unliganded ERα, and promotes gene regulatory effects that are predicted to counter the effects of unliganded ERα. These results reveal that the unliganded form of ERα is not inert, but significantly impacts gene expression and physiology of vascular cells. Furthermore, they indicate that the cardiovascular protective effects of estrogen may be connected to its ability to counteract these effects of unliganded ERα.

iFORM: Incorporating Find Occurrence of Regulatory Motifs

Accurately identifying the binding sites of transcription factors (TFs) is crucial to understanding the mechanisms of transcriptional regulation and human disease. We present incorporating Find Occurrence of Regulatory Motifs (iFORM), an easy-to-use and efficient tool for scanning DNA sequences with TF motifs described as position weight matrices (PWMs). Both performance assessment with a receiver operating characteristic (ROC) curve and a correlation-based approach demonstrated that iFORM achieves higher accuracy and sensitivity by integrating five classical motif discovery programs using Fisher’s combined probability test. We have used iFORM to provide accurate results on a variety of data in the ENCODE Project and the NIH Roadmap Epigenomics Project, and the tool has demonstrated its utility in further elucidating individual roles of functional elements. Both the source and binary codes for iFORM can be freely accessed at https://github.com/wenjiegroup/iFORM. The identified TF binding sites across human cell and tissue types using iFORM have been deposited in the Gene Expression Omnibus under the accession ID GSE53962.

Broad histone H3K4me3 domains in mouse oocytes modulate maternal-to-zygotic transition

Maternal-to-zygotic transition (MZT) is essential for the formation of a new individual, but is still poorly understood despite recent progress in analysis of gene expression and DNA methylation in early embryogenesis. Dynamic histone modifications may have important roles in MZT, but direct measurements of chromatin states have been hindered by technical difficulties in profiling histone modifications from small quantities of cells. Recent improvements allow for 500 cell-equivalents of chromatin per reaction, but require 10,000 cells for initial steps or require a highly specialized microfluidics device that is not readily available. We developed a micro-scale chromatin immunoprecipitation and sequencing (μChIP-seq) method, which we used to profile genome-wide histone H3 lysine methylation (H3K4me3) and acetylation (H3K27ac) in mouse immature and metaphase II oocytes and in 2-cell and 8-cell embryos. Notably, we show that ~22% of the oocyte genome is associated with broad H3K4me3 domains that are anti-correlated with DNA methylation. The H3K4me3 signal becomes confined to transcriptional-start-site regions in 2-cell embryos, concomitant with the onset of major zygotic genome activation. Active removal of broad H3K4me3 domains by the lysine demethylases KDM5A and KDM5B is required for normal zygotic genome activation and is essential for early embryo development. Our results provide insight into the onset of the developmental program in mouse embryos and demonstrate a role for broad H3K4me3 domains in MZT.

ER Alpha Rapid Signaling Is Required for Estrogen Induced Proliferation and Migration of Vascular Endothelial Cells

Estrogen promotes the proliferation and migration of vascular endothelial cells (ECs), which likely underlies its ability to accelerate re-endothelialization and reduce adverse remodeling after vascular injury. In previous studies, we have shown that the protective effects of E2 (the active endogenous form of estrogen) in vascular injury require the estrogen receptor alpha (ERα). ERα transduces the effects of estrogen via a classical DNA binding, "genomic" signaling pathway and via a more recently-described "rapid" signaling pathway that is mediated by a subset of ERα localized to the cell membrane. However, which of these pathways mediates the effects of estrogen on endothelial cells is poorly understood. Here we identify a triple point mutant version of ERα (KRR ERα) that is specifically defective in rapid signaling, but is competent to regulate transcription through the "genomic" pathway. We find that in ECs expressing wild type ERα, E2 regulates many genes involved in cell migration and proliferation, promotes EC migration and proliferation, and also blocks the adhesion of monocytes to ECs. ECs expressing KRR mutant ERα, however, lack all of these responses. These observations establish KRR ERα as a novel tool that could greatly facilitate future studies into the vascular and non-vascular functions of ERα rapid signaling. Further, they support that rapid signaling through ERα is essential for many of the transcriptional and physiological responses of ECs to E2, and that ERα rapid signaling in ECs, in vivo, may be critical for the vasculoprotective and anti-inflammatory effects of estrogen.

Small Genetic Circuits and MicroRNAs: Big Players in Polymerase II Transcriptional Control in Plants

RNA Polymerase II (Pol II) regulatory cascades involving transcription factors (TFs) and their targets orchestrate the genetic circuitry of every eukaryotic organism. In order to understand how these cascades function, they can be dissected into small genetic networks, each containing just a few Pol II transcribed genes, that generate specific signal-processing outcomes. Small RNA regulatory circuits involve direct regulation of a small RNA by a TF and/or direct regulation of a TF by a small RNA and have been shown to play unique roles in many organisms. Here, we will focus on small RNA regulatory circuits containing Pol II transcribed microRNAs (miRNAs). While the role of miRNA-containing regulatory circuits as modular building blocks for the function of complex networks has long been on the forefront of studies in the animal kingdom, plant studies are poised to take a lead role in this area because of their advantages in probing transcriptional and posttranscriptional control of Pol II genes. The relative simplicity of tissue- and cell-type organization, miRNA targeting, and genomic structure make the Arabidopsis thaliana plant model uniquely amenable for small RNA regulatory circuit studies in a multicellular organism. In this Review, we cover analysis, tools, and validation methods for probing the component interactions in miRNA-containing regulatory circuits. We then review the important roles that plant miRNAs are playing in these circuits and summarize methods for the identification of small genetic circuits that strongly influence plant function. We conclude by noting areas of opportunity where new plant studies are imminently needed.

The glucose-sensing transcription factor MLX promotes myogenesis via myokine signaling

In this study, Hunt et. al. provide novel insight into the regulation of glucose-induced myogenesis. They demonstrate that changes in glucose levels regulate myogenesis by increasing the activity of the glucose-responsive transcription factor MLX, which is necessary and sufficient for myoblast fusion and differentiation.

Metabolic stress and changes in nutrient levels modulate many aspects of skeletal muscle function during aging and disease. Growth factors and cytokines secreted by skeletal muscle, known as myokines, are important signaling factors, but it is largely unknown whether they modulate muscle growth and differentiation in response to nutrients. Here, we found that changes in glucose levels increase the activity of the glucose-responsive transcription factor MLX (Max-like protein X), which promotes and is necessary for myoblast fusion. MLX promotes myogenesis not via an adjustment of glucose metabolism but rather by inducing the expression of several myokines, including insulin-like growth factor 2 (IGF2), whereas RNAi and dominant-negative MLX reduce IGF2 expression and block myogenesis. This phenotype is rescued by conditioned medium from control muscle cells and by recombinant IGF2, which activates the myogenic kinase Akt. Importantly, MLX-null mice display decreased IGF2 induction and diminished muscle regeneration in response to injury, indicating that the myogenic function of MLX is manifested in vivo. Thus, glucose is a signaling molecule that regulates myogenesis and muscle regeneration via MLX/IGF2/Akt signaling.

Increased mitochondrial function downstream from KDM5A histone demethylase rescues differentiation in pRB-deficient cells

The retinoblastoma tumor suppressor protein pRb restricts cell growth through inhibition of cell cycle progression. Increasing evidence suggests that pRb also promotes differentiation, but the mechanisms are poorly understood, and the key question remains as to how differentiation in tumor cells can be enhanced in order to diminish their aggressive potential. Previously, we identified the histone demethylase KDM5A (lysine [K]-specific demethylase 5A), which demethylates histone H3 on Lys4 (H3K4), as a pRB-interacting protein counteracting pRB's role in promoting differentiation. Here we show that loss of Kdm5a restores differentiation through increasing mitochondrial respiration. This metabolic effect is both necessary and sufficient to induce the expression of a network of cell type-specific signaling and structural genes. Importantly, the regulatory functions of pRB in the cell cycle and differentiation are distinct because although restoring differentiation requires intact mitochondrial function, it does not necessitate cell cycle exit. Cells lacking Rb1 exhibit defective mitochondria and decreased oxygen consumption. Kdm5a is a direct repressor of metabolic regulatory genes, thus explaining the compensatory role of Kdm5a deletion in restoring mitochondrial function and differentiation. Significantly, activation of mitochondrial function by the mitochondrial biogenesis regulator Pgc-1α (peroxisome proliferator-activated receptor γ-coactivator 1α; also called PPARGC1A) a coactivator of the Kdm5a target genes, is sufficient to override the differentiation block. Overexpression of Pgc-1α, like KDM5A deletion, inhibits cell growth in RB-negative human cancer cell lines. The rescue of differentiation by loss of KDM5A or by activation of mitochondrial biogenesis reveals the switch to oxidative phosphorylation as an essential step in restoring differentiation and a less aggressive cancer phenotype.

The transcriptional repressor HDAC7 promotes apoptosis and c-Myc downregulation in particular types of leukemia and lymphoma

The generation of B cells is a complex process requiring several cellular transitions, including cell commitment and differentiation. Proper transcriptional control to establish the genetic programs characteristic of each cellular stage is essential for the correct development of B lymphocytes. Deregulation of these particular transcriptional programs may result in a block in B-cell maturation, contributing to the development of hematological malignancies such as leukemia and lymphoma. However, very little is currently known about the role of transcriptional repressors in normal and aberrant B lymphopoiesis. Here we report that histone deacetylase 7 (HDAC7) is underexpressed in pro-B acute lymphoblastic leukemia (pro-B-ALL) and Burkitt lymphoma. Ectopic expression of HDAC7 induces apoptosis, leads to the downregulation of c-Myc and inhibits the oncogenic potential of cells in vivo, in a xenograft model. Most significantly, we have observed low levels of HDAC7 expression in B-ALL patient samples, which is correlated with the increased levels of c-Myc. From a mechanistic angle, we show that ectopically expressed HDAC7 localizes to the nucleus and interacts with the transcription factor myocyte enhancer factor C (MEF2C) and the corepressors HDAC3 and SMRT. Accordingly, both the HDAC7–MEF2C interaction domain as well as its catalytic domain are involved in the reduced cell viability induced by HDAC7. We conclude that HDAC7 has a potent anti-oncogenic effect on specific B-cell malignancies, indicating that its deregulation may contribute to the pathogenesis of the disease.

Research resource: Aorta- and liver-specific ERα-binding patterns and gene regulation by estrogen

Estrogen has vascular protective effects in premenopausal women and in women younger than 60 years who are receiving hormone replacement therapy. However, estrogen also increases the risks of breast and uterine cancers and of venous thromboses linked to up-regulation of coagulation factors in the liver. In mouse models, the vasculoprotective effects of estrogen are mediated by the estrogen receptor α (ERα) transcription factor. Here, through next-generation sequencing approaches, we show that almost all of the genes regulated by 17β-estradiol (E2) differ between mouse aorta and mouse liver, ex vivo, and that this difference is associated with a distinct genomewide distribution of ERα on chromatin. Bioinformatic analysis of E2-regulated promoters and ERα binding site sequences identify several transcription factors that may determine the tissue specificity of ERα binding and E2-regulated genes, including the enrichment of NF-κB, AML1, and AP1 sites in the promoters of E2 down-regulated inflammatory genes in aorta but not liver. The possible vascular-specific functions of these factors suggest ways in which the protective effects of estrogen could be promoted in the vasculature without incurring negative effects in other tissues.

Nucleosome eviction and multiple co-factor binding predict estrogen-receptor-alpha-associated long-range interactions

Many enhancers regulate their target genes via long-distance interactions. High-throughput experiments like ChIA-PET have been developed to map such largely cell-type-specific interactions between cis-regulatory elements genome-widely. In this study, we integrated multiple types of data in order to reveal the general hidden patterns embedded in the ChIA-PET data. We found characteristic distance features related to promoter-promoter, enhancer-enhancer and insulator-insulator interactions. Although a protein may have many binding sites along the genome, our hypothesis is that those sites that share certain open chromatin structure can accommodate relatively larger protein complex consisting of specific regulatory and 'bridging' factors, and may be more likely to form robust long-range deoxyribonucleic acid (DNA) loops. This hypothesis was validated in the estrogen receptor alpha (ERα) ChIA-PET data. An efficient classifier was built to predict ERα-associated long-range interactions solely from the related ChIP-seq data, hence linking distal ERα-dependent enhancers to their target genes. We further applied the classifier to generate additional novel interactions, which were undetected in the original ChIA-PET paper but were validated by other independent experiments. Our work provides a new insight into the long-range chromatin interactions through deeper and integrative ChIA-PET data analysis and demonstrates DNA looping predictability from ordinary ChIP-seq data.

Regulatory modules controlling maize inflorescence architecture

Genetic control of branching is a primary determinant of yield, regulating seed number and harvesting ability, yet little is known about the molecular networks that shape grain-bearing inflorescences of cereal crops. Here, we used the maize (Zea mays) inflorescence to investigate gene networks that modulate determinacy, specifically the decision to allow branch growth. We characterized developmental transitions by associating spatiotemporal expression profiles with morphological changes resulting from genetic perturbations that disrupt steps in a pathway controlling branching. Developmental dynamics of genes targeted in vivo by the transcription factor RAMOSA1, a key regulator of determinacy, revealed potential mechanisms for repressing branches in distinct stem cell populations, including interactions with KNOTTED1, a master regulator of stem cell maintenance. Our results uncover discrete developmental modules that function in determining grass-specific morphology and provide a basis for targeted crop improvement and translation to other cereal crops with comparable inflorescence architectures.

Genome-wide computational prediction and analysis of core promoter elements across plant monocots and dicots

Transcription initiation, essential to gene expression regulation, involves recruitment of basal transcription factors to the core promoter elements (CPEs). The distribution of currently known CPEs across plant genomes is largely unknown. This is the first large scale genome-wide report on the computational prediction of CPEs across eight plant genomes to help better understand the transcription initiation complex assembly. The distribution of thirteen known CPEs across four monocots (Brachypodium distachyon, Oryza sativa ssp. japonica, Sorghum bicolor, Zea mays) and four dicots (Arabidopsis thaliana, Populus trichocarpa, Vitis vinifera, Glycine max) reveals the structural organization of the core promoter in relation to the TATA-box as well as with respect to other CPEs. The distribution of known CPE motifs with respect to transcription start site (TSS) exhibited positional conservation within monocots and dicots with slight differences across all eight genomes. Further, a more refined subset of annotated genes based on orthologs of the model monocot (O. sativa ssp. japonica) and dicot (A. thaliana) genomes supported the positional distribution of these thirteen known CPEs. DNA free energy profiles provided evidence that the structural properties of promoter regions are distinctly different from that of the non-regulatory genome sequence. It also showed that monocot core promoters have lower DNA free energy than dicot core promoters. The comparison of monocot and dicot promoter sequences highlights both the similarities and differences in the core promoter architecture irrespective of the species-specific nucleotide bias. This study will be useful for future work related to genome annotation projects and can inspire research efforts aimed to better understand regulatory mechanisms of transcription.

Computational identification of active enhancers in model organisms

As a class of cis-regulatory elements, enhancers were first identified as the genomic regions that are able to markedly increase the transcription of genes nearly 30years ago. Enhancers can regulate gene expression in a cell-type specific and developmental stage specific manner. Although experimental technologies have been developed to identify enhancers genome-wide, the design principle of the regulatory elements and the way they rewire the transcriptional regulatory network tempo-spatially are far from clear. At present, developing predictive methods for enhancers, particularly for the cell-type specific activity of enhancers, is central to computational biology. In this review, we survey the current computational approaches for active enhancer prediction and discuss future directions.

YY1TargetDB: an integral information resource for Yin Yang 1 target loci

Yin Yang 1 (YY1), a ubiquitously expressed transcription factor, plays a critical role in regulating cell development, differentiation, cellular proliferation and tumorigenesis. Previous studies identified many YY1-regulated target genes in both human and mouse. Emerging global mapping by Chromatin ImmnoPrecipitation (ChIP)-based high-throughput experiments indicate that YY1 binds to a vast number of loci genome-wide. However, the information is widely scattered in many disparate poorly cross-indexed literatures; a large portion was only published recently by the ENCODE consortium with limited annotation. A centralized database, which annotates and organizes YY1-binding loci and target motifs in a systematic way with easy access, will be valuable resources for the research community. We therefore implemented a web-based YY1 Target loci Database (YY1TargetDB). This database contains YY1-binding loci (binding peaks) from ChIP-seq and ChIP-on-chip experiments, computationally predicated YY1 and cofactor motifs within each locus. It also collects the experimentally verified YY1-binding motifs from individual researchers. The current version of YY1TargetDB contains 92 314 binding loci identified by ChIP-based experiments; 157 200 YY1-binding motifs in which 42 are experimentally verified and 157 158 are computationally predicted; and 130 759 binding motifs for 47 cofactors.

Database URL:http://www.myogenesisdb.org/YY1TargetDB

The B cell transcription program mediates hypomethylation and overexpression of key genes in Epstein-Barr virus-associated proliferative conversion

BACKGROUND

Epstein-Barr virus (EBV) infection is a well characterized etiopathogenic factor for a variety of immune-related conditions, including lymphomas, lymphoproliferative disorders and autoimmune diseases. EBV-mediated transformation of resting B cells to proliferating lymphoblastoid cells occurs in early stages of infection and is an excellent model for investigating the mechanisms associated with acquisition of unlimited growth.

RESULTS

We investigated the effects of experimental EBV infection of B cells on DNA methylation profiles by using high-throughput analysis. Remarkably, we observed hypomethylation of around 250 genes, but no hypermethylation. Hypomethylation did not occur at repetitive sequences, consistent with the absence of genomic instability in lymphoproliferative cells. Changes in methylation only occurred after cell divisions started, without the participation of the active demethylation machinery, and were concomitant with acquisition by B cells of the ability to proliferate. Gene Ontology analysis, expression profiling, and high-throughput analysis of the presence of transcription factor binding motifs and occupancy revealed that most genes undergoing hypomethylation are active and display the presence of NF-κB p65 and other B cell-specific transcription factors. Promoter hypomethylation was associated with upregulation of genes relevant for the phenotype of proliferating lymphoblasts. Interestingly, pharmacologically induced demethylation increased the efficiency of transformation of resting B cells to lymphoblastoid cells, consistent with productive cooperation between hypomethylation and lymphocyte proliferation.

CONCLUSIONS

Our data provide novel clues on the role of the B cell transcription program leading to DNA methylation changes, which we find to be key to the EBV-associated conversion of resting B cells to proliferating lymphoblasts.

PU.1 target genes undergo Tet2-coupled demethylation and DNMT3b-mediated methylation in monocyte-to-osteoclast differentiation

BACKGROUND

DNA methylation is a key epigenetic mechanism for driving and stabilizing cell-fate decisions. Local deposition and removal of DNA methylation are tightly coupled with transcription factor binding, although the relationship varies with the specific differentiation process. Conversion of monocytes to osteoclasts is a unique terminal differentiation process within the hematopoietic system. This differentiation model is relevant to autoimmune disease and cancer, and there is abundant knowledge on the sets of transcription factors involved.

RESULTS

Here we focused on DNA methylation changes during osteoclastogenesis. Hypermethylation and hypomethylation changes took place in several thousand genes, including all relevant osteoclast differentiation and function categories. Hypomethylation occurred in association with changes in 5-hydroxymethylcytosine, a proposed intermediate toward demethylation. Transcription factor binding motif analysis revealed an over-representation of PU.1, NF-κB, and AP-1 (Jun/Fos) binding motifs in genes undergoing DNA methylation changes. Among these, only PU.1 motifs were significantly enriched in both hypermethylated and hypomethylated genes; ChIP-seq data analysis confirmed its association to both gene sets. Moreover, PU.1 interacts with both DNMT3b and TET2, suggesting its participation in driving hypermethylation and hydroxymethylation-mediated hypomethylation. Consistent with this, siRNA-mediated PU.1 knockdown in primary monocytes impaired the acquisition of DNA methylation and expression changes, and reduced the association of TET2 and DNMT3b at PU.1 targets during osteoclast differentiation.

CONCLUSIONS

The work described here identifies key changes in DNA methylation during monocyte-to-osteoclast differentiation and reveals novel roles for PU.1 in this process.

Rapid estrogen receptor signaling is essential for the protective effects of estrogen against vascular injury

BACKGROUND

Clinical trial and epidemiological data support that the cardiovascular effects of estrogen are complex, including a mixture of both potentially beneficial and harmful effects. In animal models, estrogen protects females from vascular injury and inhibits atherosclerosis. These effects are mediated by estrogen receptors (ERs), which, when bound to estrogen, can bind to DNA to directly regulate transcription. ERs can also activate several cellular kinases by inducing a rapid nonnuclear signaling cascade. However, the biological significance of this rapid signaling pathway has been unclear.

METHODS AND RESULTS

In the present study, we develop a novel transgenic mouse in which rapid signaling is blocked by overexpression of a peptide that prevents ERs from interacting with the scaffold protein striatin (the disrupting peptide mouse). Microarray analysis of ex vivo treated mouse aortas demonstrates that rapid ER signaling plays an important role in estrogen-mediated gene regulatory responses. Disruption of ER-striatin interactions also eliminates the ability of estrogen to stimulate cultured endothelial cell migration and to inhibit cultured vascular smooth muscle cell growth. The importance of these findings is underscored by in vivo experiments demonstrating loss of estrogen-mediated protection against vascular injury in the disrupting peptide mouse after carotid artery wire injury.

CONCLUSIONS

Taken together, these results support the concept that rapid, nonnuclear ER signaling contributes to the transcriptional regulatory functions of ER and is essential for many of the vasoprotective effects of estrogen. These findings also identify the rapid ER signaling pathway as a potential target for the development of novel therapeutic agents.

Bivalent-like chromatin markers are predictive for transcription start site distribution in human

Deep sequencing of 5′ capped transcripts has revealed a variety of transcription initiation patterns, from narrow, focused promoters to wide, broad promoters. Attempts have already been made to model empirically classified patterns, but virtually no quantitative models for transcription initiation have been reported. Even though both genetic and epigenetic elements have been associated with such patterns, the organization of regulatory elements is largely unknown. Here, linear regression models were derived from a pool of regulatory elements, including genomic DNA features, nucleosome organization, and histone modifications, to predict the distribution of transcription start sites (TSS). Importantly, models including both active and repressive histone modification markers, e.g. H3K4me3 and H4K20me1, were consistently found to be much more predictive than models with only single-type histone modification markers, indicating the possibility of “bivalent-like” epigenetic control of transcription initiation. The nucleosome positions are proposed to be coded in the active component of such bivalent-like histone modification markers. Finally, we demonstrated that models trained on one cell type could successfully predict TSS distribution in other cell types, suggesting that these models may have a broader application range.

Characterization of miRNAs in response to short-term waterlogging in three inbred lines of Zea mays

Waterlogging of plants leads to low oxygen levels (hypoxia) in the roots and causes a metabolic switch from aerobic respiration to anaerobic fermentation that results in rapid changes in gene transcription and protein synthesis. Our research seeks to characterize the microRNA-mediated gene regulatory networks associated with short-term waterlogging. MicroRNAs (miRNAs) are small non-coding RNAs that regulate many genes involved in growth, development and various biotic and abiotic stress responses. To characterize the involvement of miRNAs and their targets in response to short-term hypoxia conditions, a quantitative real time PCR (qRT-PCR) assay was used to quantify the expression of the 24 candidate mature miRNA signatures (22 known and 2 novel mature miRNAs, representing 66 miRNA loci) and their 92 predicted targets in three inbred Zea mays lines (waterlogging tolerant Hz32, mid-tolerant B73, and sensitive Mo17). Based on our studies, miR159, miR164, miR167, miR393, miR408 and miR528, which are mainly involved in root development and stress responses, were found to be key regulators in the post-transcriptional regulatory mechanisms under short-term waterlogging conditions in three inbred lines. Further, computational approaches were used to predict the stress and development related cis-regulatory elements on the promoters of these miRNAs; and a probable miRNA-mediated gene regulatory network in response to short-term waterlogging stress was constructed. The differential expression patterns of miRNAs and their targets in these three inbred lines suggest that the miRNAs are active participants in the signal transduction at the early stage of hypoxia conditions via a gene regulatory network; and crosstalk occurs between different biochemical pathways.

Genomic approaches towards finding cis-regulatory modules in animals

Differential gene expression is the fundamental mechanism underlying animal development and cell differentiation. However, it is a challenge to identify comprehensively and accurately the DNA sequences that are required to regulate gene expression: namely, cis-regulatory modules (CRMs). Three major features, either singly or in combination, are used to predict CRMs: clusters of transcription factor binding site motifs, non-coding DNA that is under evolutionary constraint and biochemical marks associated with CRMs, such as histone modifications and protein occupancy. The validation rates for predictions indicate that identifying diagnostic biochemical marks is the most reliable method, and understanding is enhanced by the analysis of motifs and conservation patterns within those predicted CRMs.

A Novel YY1-miR-1 regulatory circuit in skeletal myogenesis revealed by genome-wide prediction of YY1-miRNA network

microRNAs (miRNAs) are non-coding RNAs that regulate gene expression post-transcriptionally, and mounting evidence supports the prevalence and functional significance of their interplay with transcription factors (TFs). Here we describe the identification of a regulatory circuit between muscle miRNAs (miR-1, miR-133 and miR-206) and Yin Yang 1 (YY1), an epigenetic repressor of skeletal myogenesis in mouse. Genome-wide identification of potential down-stream targets of YY1 by combining computational prediction with expression profiling data reveals a large number of putative miRNA targets of YY1 during skeletal myoblasts differentiation into myotubes with muscle miRs ranking on top of the list. The subsequent experimental results demonstrate that YY1 indeed represses muscle miRs expression in myoblasts and the repression is mediated through multiple enhancers and recruitment of Polycomb complex to several YY1 binding sites. YY1 regulating miR-1 is functionally important for both C2C12 myogenic differentiation and injury-induced muscle regeneration. Furthermore, we demonstrate that miR-1 in turn targets YY1, thus forming a negative feedback loop. Together, these results identify a novel regulatory circuit required for skeletal myogenesis and reinforce the idea that regulatory circuitries involving miRNAs and TFs are prevalent mechanisms.

Oncogenic activation of FOXR1 by 11q23 intrachromosomal deletion-fusions in neuroblastoma

Neuroblastoma tumors frequently show loss of heterozygosity of chromosome 11q with a shortest region of overlap in the 11q23 region. These deletions are thought to cause inactivation of tumor suppressor genes leading to haploinsufficiency. Alternatively, micro-deletions could lead to gene fusion products that are tumor driving. To identify such events we analyzed a series of neuroblastomas by comparative genomic hybridization and single-nucleotide polymorphism arrays and integrated these data with Affymetrix mRNA profiling data with the bioinformatic tool R2 (http://r2.amc.nl). We identified three neuroblastoma samples with small interstitial deletions at 11q23, upstream of the forkhead-box R1 transcription factor (FOXR1). Genes at the proximal side of the deletion were fused to FOXR1, resulting in fusion transcripts of MLL-FOXR1 and PAFAH1B2-FOXR1. FOXR1 expression has only been detected in early embryogenesis. Affymetrix microarray analysis showed high FOXR1 mRNA expression exclusively in the neuroblastomas with micro-deletions and rare cases of other tumor types, including osteosarcoma cell line HOS. RNAi silencing of FOXR1 strongly inhibited proliferation of HOS cells and triggered apoptosis. Expression profiling of these cells and reporter assays suggested that FOXR1 is a negative regulator of fork-head box factor-mediated transcription. The neural crest stem cell line JoMa1 proliferates in culture conditional to activity of a MYC-ER transgene. Over-expression of the wild-type FOXR1 could functionally replace MYC and drive proliferation of JoMa1. We conclude that FOXR1 is recurrently activated in neuroblastoma by intrachromosomal deletion/fusion events, resulting in overexpression of fusion transcripts. Forkhead-box transcription factors have not been previously implicated in neuroblastoma pathogenesis. Furthermore, this is the first identification of intrachromosomal fusion genes in neuroblastoma.

Computational identification of transcriptional regulators in human endotoxemia

One of the great challenges in the post-genomic era is to decipher the underlying principles governing the dynamics of biological responses. As modulating gene expression levels is among the key regulatory responses of an organism to changes in its environment, identifying biologically relevant transcriptional regulators and their putative regulatory interactions with target genes is an essential step towards studying the complex dynamics of transcriptional regulation. We present an analysis that integrates various computational and biological aspects to explore the transcriptional regulation of systemic inflammatory responses through a human endotoxemia model. Given a high-dimensional transcriptional profiling dataset from human blood leukocytes, an elementary set of temporal dynamic responses which capture the essence of a pro-inflammatory phase, a counter-regulatory response and a dysregulation in leukocyte bioenergetics has been extracted. Upon identification of these expression patterns, fourteen inflammation-specific gene batteries that represent groups of hypothetically ‘coregulated’ genes are proposed. Subsequently, statistically significant cis-regulatory modules (CRMs) are identified and decomposed into a list of critical transcription factors (34) that are validated largely on primary literature. Finally, our analysis further allows for the construction of a dynamic representation of the temporal transcriptional regulatory program across the host, deciphering possible combinatorial interactions among factors under which they might be active. Although much remains to be explored, this study has computationally identified key transcription factors and proposed a putative time-dependent transcriptional regulatory program associated with critical transcriptional inflammatory responses. These results provide a solid foundation for future investigations to elucidate the underlying transcriptional regulatory mechanisms under the host inflammatory response. Also, the assumption that coexpressed genes that are functionally relevant are more likely to share some common transcriptional regulatory mechanism seems to be promising, making the proposed framework become essential in unravelling context-specific transcriptional regulatory interactions underlying diverse mammalian biological processes.

Finding significant matches of position weight matrices in linear time

Position weight matrices are an important method for modeling signals or motifs in biological sequences, both in DNA and protein contexts. In this paper, we present fast algorithms for the problem of finding significant matches of such matrices. Our algorithms are of the online type, and they generalize classical multipattern matching, filtering, and superalphabet techniques of combinatorial string matching to the problem of weight matrix matching. Several variants of the algorithms are developed, including multiple matrix extensions that perform the search for several matrices in one scan through the sequence database. Experimental performance evaluation is provided to compare the new techniques against each other as well as against some other online and index-based algorithms proposed in the literature. Compared to the brute-force O(mn) approach, our solutions can be faster by a factor that is proportional to the matrix length m. Our multiple-matrix filtration algorithm had the best performance in the experiments. On a current PC, this algorithm finds significant matches (p = 0.0001) of the 123 JASPAR matrices in the human genome in about 18 minutes.

Ubiquitin accumulation in autophagy-deficient mice is dependent on the Nrf2-mediated stress response pathway: a potential role for protein aggregation in autophagic substrate selection

Inactivation of the essential autophagy gene Atg5 results in selective accumulation of aggregation-prone proteins independently of substrate ubiquitination.

Genetic ablation of autophagy in mice leads to liver and brain degeneration accompanied by the appearance of ubiquitin (Ub) inclusions, which has been considered to support the hypothesis that ubiquitination serves as a cis-acting signal for selective autophagy. We show that tissue-specific disruption of the essential autophagy genes Atg5 and Atg7 leads to the accumulation of all detectable Ub–Ub topologies, arguing against the hypothesis that any particular Ub linkage serves as a specific autophagy signal. The increase in Ub conjugates in Atg7^−/− liver and brain is completely suppressed by simultaneous knockout of either p62 or Nrf2. We exploit a novel assay for selective autophagy in cell culture, which shows that inactivation of Atg5 leads to the selective accumulation of aggregation-prone proteins, and this does not correlate with an increase in substrate ubiquitination. We propose that protein oligomerization drives autophagic substrate selection and that the accumulation of poly-Ub chains in autophagy-deficient circumstances is an indirect consequence of activation of Nrf2-dependent stress response pathways.

Assessing computational methods of cis-regulatory module prediction

Computational methods attempting to identify instances of cis-regulatory modules (CRMs) in the genome face a challenging problem of searching for potentially interacting transcription factor binding sites while knowledge of the specific interactions involved remains limited. Without a comprehensive comparison of their performance, the reliability and accuracy of these tools remains unclear. Faced with a large number of different tools that address this problem, we summarized and categorized them based on search strategy and input data requirements. Twelve representative methods were chosen and applied to predict CRMs from the Drosophila CRM database REDfly, and across the human ENCODE regions. Our results show that the optimal choice of method varies depending on species and composition of the sequences in question. When discriminating CRMs from non-coding regions, those methods considering evolutionary conservation have a stronger predictive power than methods designed to be run on a single genome. Different CRM representations and search strategies rely on different CRM properties, and different methods can complement one another. For example, some favour homotypical clusters of binding sites, while others perform best on short CRMs. Furthermore, most methods appear to be sensitive to the composition and structure of the genome to which they are applied. We analyze the principal features that distinguish the methods that performed well, identify weaknesses leading to poor performance, and provide a guide for users. We also propose key considerations for the development and evaluation of future CRM-prediction methods.

Transcriptional regulation involves multiple transcription factors binding to DNA sequences. A limited repertoire of transcription factors performs this complex regulatory step through various spatial and temporal interactions between themselves and their binding sites. These transcription factor binding interactions are clustered as distinct modules: cis-regulatory modules (CRMs). Computational methods attempting to identify instances of CRMs in the genome face a challenging problem because a majority of these interactions between transcription factors remain unknown. To investigate the reliability and accuracy of these methods, we chose twelve representative methods and applied them to predict CRMs on both the fly and human genomes. Our results show that the optimal choice of method varies depending on species and composition of the sequences in question. Different CRM representations and search strategies rely on different CRM properties, and different methods can complement one another. We provide a guide for users and key considerations for developers. We also expect that, along with new technology generating new types of genomic data, future CRM prediction methods will be able to reveal transcription binding interactions in three-dimensional space.

Biological reprogramming in acquired resistance to endocrine therapy of breast cancer

Endocrine therapies targeting the proliferative effect of 17β-estradiol through estrogen receptor α (ERα) are the most effective systemic treatment of ERα-positive breast cancer. However, most breast tumors initially responsive to these therapies develop resistance through molecular mechanisms that are not yet fully understood. The long-term estrogen-deprived (LTED) MCF7 cell model has been proposed to recapitulate acquired resistance to aromatase inhibitors in postmenopausal women. To elucidate this resistance, genomic, transcriptomic and molecular data were integrated into the time course of MCF7-LTED adaptation. Dynamic and widespread genomic changes were observed, including amplification of the ESR1 locus consequently linked to an increase in ERα. Dynamic transcriptomic profiles were also observed that correlated significantly with genomic changes and were predicted to be influenced by transcription factors known to be involved in acquired resistance or cell proliferation (for example, interferon regulatory transcription factor 1 and E2F1, respectively) but, notably, not by canonical ERα transcriptional function. Consistently, at the molecular level, activation of growth factor signaling pathways by EGFR/ERBB/AKT and a switch from phospho-Ser118 (pS118)- to pS167-ERα were observed during MCF7-LTED adaptation. Evaluation of relevant clinical settings identified significant associations between MCF7-LTED and breast tumor transcriptome profiles that characterize ERα-negative status, early response to letrozole and tamoxifen, and recurrence after tamoxifen treatment. In accordance with these profiles, MCF7-LTED cells showed increased sensitivity to inhibition of FGFR-mediated signaling with PD173074. This study provides mechanistic insight into acquired resistance to endocrine therapies of breast cancer and highlights a potential therapeutic strategy.

Functional evolution of cis-regulatory modules at a homeotic gene in Drosophila

It is a long-held belief in evolutionary biology that the rate of molecular evolution for a given DNA sequence is inversely related to the level of functional constraint. This belief holds true for the protein-coding homeotic (Hox) genes originally discovered in Drosophila melanogaster. Expression of the Hox genes in Drosophila embryos is essential for body patterning and is controlled by an extensive array of cis-regulatory modules (CRMs). How the regulatory modules functionally evolve in different species is not clear. A comparison of the CRMs for the Abdominal-B gene from different Drosophila species reveals relatively low levels of overall sequence conservation. However, embryonic enhancer CRMs from other Drosophila species direct transgenic reporter gene expression in the same spatial and temporal patterns during development as their D. melanogaster orthologs. Bioinformatic analysis reveals the presence of short conserved sequences within defined CRMs, representing gap and pair-rule transcription factor binding sites. One predicted binding site for the gap transcription factor KRUPPEL in the IAB5 CRM was found to be altered in Superabdominal (Sab) mutations. In Sab mutant flies, the third abdominal segment is transformed into a copy of the fifth abdominal segment. A model for KRUPPEL-mediated repression at this binding site is presented. These findings challenge our current understanding of the relationship between sequence evolution at the molecular level and functional activity of a CRM. While the overall sequence conservation at Drosophila CRMs is not distinctive from neighboring genomic regions, functionally critical transcription factor binding sites within embryonic enhancer CRMs are highly conserved. These results have implications for understanding mechanisms of gene expression during embryonic development, enhancer function, and the molecular evolution of eukaryotic regulatory modules.

Transcription factor site dependencies in human, mouse and rat genomes

BACKGROUND

It is known that transcription factors frequently act together to regulate gene expression in eukaryotes. In this paper we describe a computational analysis of transcription factor site dependencies in human, mouse and rat genomes.

RESULTS

Our approach for quantifying tendencies of transcription factor binding sites to co-occur is based on a binding site scoring function which incorporates dependencies between positions, the use of information about the structural class of each transcription factor (major/minor groove binder), and also considered the possible implications of varying GC content of the sequences. Significant tendencies (dependencies) have been detected by non-parametric statistical methodology (permutation tests). Evaluation of obtained results has been performed in several ways: reports from literature (many of the significant dependencies between transcription factors have previously been confirmed experimentally); dependencies between transcription factors are not biased due to similarities in their DNA-binding sites; the number of dependent transcription factors that belong to the same functional and structural class is significantly higher than would be expected by chance; supporting evidence from GO clustering of targeting genes. Based on dependencies between two transcription factor binding sites (second-order dependencies), it is possible to construct higher-order dependencies (networks). Moreover results about transcription factor binding sites dependencies can be used for prediction of groups of dependent transcription factors on a given promoter sequence. Our results, as well as a scanning tool for predicting groups of dependent transcription factors binding sites are available on the Internet.

CONCLUSION

We show that the computational analysis of transcription factor site dependencies is a valuable complement to experimental approaches for discovering transcription regulatory interactions and networks. Scanning promoter sequences with dependent groups of transcription factor binding sites improve the quality of transcription factor predictions.