Dissecting the retinoid-induced differentiation of F9 embryonal stem cells by integrative genomics

Nuclear and extra-nuclear effects of retinoid acid receptors: how they are interconnected

The nuclear retinoic acid receptors (RAR α, β and γ) and their isoforms are ligand-dependent regulators of transcription Transcription , which mediate the effects of all-trans retinoic acid (RA), the active endogenous metabolite of Vitamin A. They heterodimerize with Retinoid X Receptors (RXRs α, β and γ), and regulate the expression of a battery of target genes Target genes involved in cell growth and differentiation Differentiation . During the two last decades, the description of the crystallographic structures of RARs, the characterization of the polymorphic response elements of their target genes Target genes , and the identification of the multiprotein complexes involved in their transcriptional activity have provided a wealth of information on their pleiotropic effects. However, the regulatory scenario became even more complicated once it was discovered that RARs are phosphoproteins and that RA can activate kinase signaling cascades via a pool of RARs present in membrane lipid rafts. Now it is known that these RA-activated kinases Kinases translocate to the nucleus where they phosphorylate RARs and other retinoid signaling factors. The phosphorylation Phosphorylation state of the RARs dictates whether the transcriptional programs which are known to be induced by RA are facilitated and/or switched on. Thus, kinase signaling pathways appear to be crucial for fine-tuning the appropriate physiological activity of RARs.

Stem cell systems informatics for advanced clinical biodiagnostics: tracing molecular signatures from bench to bedside

Development of innovative high throughput technologies has enabled a variety of molecular landscapes to be interrogated with an unprecedented degree of detail. Emergence of next generation nucleotide sequencing methods, advanced proteomic techniques, and metabolic profiling approaches continue to produce a wealth of biological data that captures molecular frameworks underlying phenotype. The advent of these novel technologies has significant translational applications, as investigators can now explore molecular underpinnings of developmental states with a high degree of resolution. Application of these leading-edge techniques to patient samples has been successfully used to unmask nuanced molecular details of disease vs healthy tissue, which may provide novel targets for palliative intervention. To enhance such approaches, concomitant development of algorithms to reprogram differentiated cells in order to recapitulate pluripotent capacity offers a distinct advantage to advancing diagnostic methodology. Bioinformatic deconvolution of several “-omic” layers extracted from reprogrammed patient cells, could, in principle, provide a means by which the evolution of individual pathology can be developmentally monitored. Significant logistic challenges face current implementation of this novel paradigm of patient treatment and care, however, several of these limitations have been successfully addressed through continuous development of cutting edge in silico archiving and processing methods. Comprehensive elucidation of genomic, transcriptomic, proteomic, and metabolomic networks that define normal and pathological states, in combination with reprogrammed patient cells are thus poised to become high value resources in modern diagnosis and prognosis of patient disease.

Characterising ChIP-seq binding patterns by model-based peak shape deconvolution

Background

Chromatin immunoprecipitation combined with massive parallel sequencing (ChIP-seq) is widely used to study protein-chromatin interactions or chromatin modifications at genome-wide level. Sequence reads that accumulate locally at the genome (peaks) reveal loci of selectively modified chromatin or specific sites of chromatin-binding factors. Computational approaches (peak callers) have been developed to identify the global pattern of these sites, most of which assess the deviation from background by applying distribution statistics.

Results

We have implemented MeDiChISeq, a regression-based approach, which - by following a learning process - defines a representative binding pattern from the investigated ChIP-seq dataset. Using this model MeDiChISeq identifies significant genome-wide patterns of chromatin-bound factors or chromatin modification. MeDiChISeq has been validated for various publicly available ChIP-seq datasets and extensively compared with other peak callers.

Conclusions

MeDiChI-Seq has a high resolution when identifying binding events, a high degree of peak-assessment reproducibility in biological replicates, a low level of false calls and a high true discovery rate when evaluated in the context of gold-standard benchmark datasets. Importantly, this approach can be applied not only to ‘sharp’ binding patterns - like those retrieved for transcription factors (TFs) - but also to the broad binding patterns seen for several histone modifications. Notably, we show that at high sequencing depths, MeDiChISeq outperforms other algorithms due to its powerful peak shape recognition capacity which facilitates discerning significant binding events from spurious background enrichment patterns that are enhanced with increased sequencing depths.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-14-834) contains supplementary material, which is available to authorized users.

Dynamics of 1α,25-dihydroxyvitamin D3-dependent chromatin accessibility of early vitamin D receptor target genes

The signaling cascade of the transcription factor vitamin D receptor (VDR) is triggered by its specific ligand 1α,25-dihydroxyvitamin D3 (1α,25(OH)2D3). In this study we demonstrate that in THP-1 human monocytic leukemia cells 87.4% of the 1034 most prominent genome-wide VDR binding sites co-localize with loci of open chromatin. At 165 of them 1α,25(OH)2D3 strongly increases chromatin accessibility and has at further 217 sites weaker effects. Interestingly, VDR binding sites in 1α,25(OH)2D3-responsive chromatin regions are far more often composed of direct repeats with 3 intervening nucleotides (DR3s) than those in ligand insensitive regions. DR3-containing VDR sites are enriched in the neighborhood of genes that are involved in controling cellular growth, while non-DR3 VDR binding is often found close to genes related to immunity. At the example of six early VDR target genes we show that the slope of their 1α,25(OH)2D3-induced transcription correlates with the basal chromatin accessibility of their major VDR binding regions. However, the chromatin loci controlling these genes are indistinguishable in their VDR association kinetics. Taken together, ligand responsive chromatin loci represent dynamically regulated contact points of VDR with the genome, from where it controls early 1α,25(OH)2D3 target genes.

Stem cell systems informatics for advanced clinical biodiagnostics: tracing molecular signatures from bench to bedside

Development of innovative high throughput technologies has enabled a variety of molecular landscapes to be interrogated with an unprecedented degree of detail. Emergence of next generation nucleotide sequencing methods, advanced proteomic techniques, and metabolic profiling approaches continue to produce a wealth of biological data that captures molecular frameworks underlying phenotype. The advent of these novel technologies has significant translational applications, as investigators can now explore molecular underpinnings of developmental states with a high degree of resolution. Application of these leading-edge techniques to patient samples has been successfully used to unmask nuanced molecular details of disease vs healthy tissue, which may provide novel targets for palliative intervention. To enhance such approaches, concomitant development of algorithms to reprogram differentiated cells in order to recapitulate pluripotent capacity offers a distinct advantage to advancing diagnostic methodology. Bioinformatic deconvolution of several "-omic" layers extracted from reprogrammed patient cells, could, in principle, provide a means by which the evolution of individual pathology can be developmentally monitored. Significant logistic challenges face current implementation of this novel paradigm of patient treatment and care, however, several of these limitations have been successfully addressed through continuous development of cutting edge in silico archiving and processing methods. Comprehensive elucidation of genomic, transcriptomic, proteomic, and metabolomic networks that define normal and pathological states, in combination with reprogrammed patient cells are thus poised to become high value resources in modern diagnosis and prognosis of patient disease.

Gene regulatory networks in plants: learning causality from time and perturbation

The goal of systems biology is to generate models for predicting how a system will react under untested conditions or in response to genetic perturbations. This paper discusses experimental and analytical approaches to deriving causal relationships in gene regulatory networks.

The elongation complex components BRD4 and MLLT3/AF9 are transcriptional coactivators of nuclear retinoid receptors

Nuclear all-trans retinoic acid receptors (RARs) initiate early transcriptional events which engage pluripotent cells to differentiate into specific lineages. RAR-controlled transactivation depends mostly on agonist-induced structural transitions in RAR C-terminus (AF-2), thus bridging coactivators or corepressors to chromatin, hence controlling preinitiation complex assembly. However, the contribution of other domains of RAR to its overall transcriptional activity remains poorly defined. A proteomic characterization of nuclear proteins interacting with RAR regions distinct from the AF-2 revealed unsuspected functional properties of the RAR N-terminus. Indeed, mass spectrometry fingerprinting identified the Bromodomain-containing protein 4 (BRD4) and ALL1-fused gene from chromosome 9 (AF9/MLLT3), known to associate with and regulates the activity of Positive Transcription Elongation Factor b (P-TEFb), as novel RAR coactivators. In addition to promoter sequences, RAR binds to genomic, transcribed regions of retinoid-regulated genes, in association with RNA polymerase II and as a function of P-TEFb activity. Knockdown of either AF9 or BRD4 expression affected differentially the neural differentiation of stem cell-like P19 cells. Clusters of retinoid-regulated genes were selectively dependent on BRD4 and/or AF9 expression, which correlated with RAR association to transcribed regions. Thus RAR establishes physical and functional links with components of the elongation complex, enabling the rapid retinoid-induced induction of genes required for neuronal differentiation. Our data thereby extends the previously known RAR interactome from classical transcriptional modulators to components of the elongation machinery, and unravel a functional role of RAR in transcriptional elongation.

Polycomb recruitment attenuates retinoic acid-induced transcription of the bivalent NR2F1 gene

Polycomb proteins play key roles in mediating epigenetic modifications that occur during cell differentiation. The Polycomb repressive complex 2 (PRC2) mediates the tri-methylation of histone H3 lysine 27 (H3K27me3). In this study, we identify a distinguishing feature of two classes of PRC2 target genes, represented by the Nr2F1 (Coup-TF1) and the Hoxa5 gene, respectively. Both genes are transcriptionally activated by all-trans retinoic acid (RA) and display increased levels of the permissive H3K9/K14ac and tri-methylated histone H3 lysine 4 epigenetic marks in response to RA. However, while in response to RA the PRC2 and H3K27me3 marks are greatly decreased at the Hoxa5 promoter, these marks are initially increased at the Nr2F1 promoter. Functional depletion of the essential PRC2 protein Suz12 by short hairpin RNA (shRNA) technology enhanced the RA-associated transcription of Nr2F1, Nr2F2, Meis1, Sox9 and BMP2, but had no effect on the Hoxa5, Hoxa1, Cyp26a1, Cyp26b1 and RARβ2 transcript levels in wild-type embryonic stem cells. We propose that PRC2 recruitment attenuates the RA-associated transcriptional activation of a subset of genes. Such a mechanism would permit the fine-tuning of transcriptional networks during differentiation.

Transcriptomic analysis of murine embryos lacking endogenous retinoic acid signaling

Retinoic acid (RA), an active derivative of the liposoluble vitamin A (retinol), acts as an important signaling molecule during embryonic development, regulating phenomenons as diverse as anterior-posterior axial patterning, forebrain and optic vesicle development, specification of hindbrain rhombomeres, pharyngeal arches and second heart field, somitogenesis, and differentiation of spinal cord neurons. This small molecule directly triggers gene activation by binding to nuclear receptors (RARs), switching them from potential repressors to transcriptional activators. The repertoire of RA-regulated genes in embryonic tissues is poorly characterized. We performed a comparative analysis of the transcriptomes of murine wild-type and Retinaldehyde Dehydrogenase 2 null-mutant (Raldh2^−/−) embryos — unable to synthesize RA from maternally-derived retinol — using Affymetrix DNA microarrays. Transcriptomic changes were analyzed in two embryonic regions: anterior tissues including forebrain and optic vesicle, and posterior (trunk) tissues, at early stages preceding the appearance of overt phenotypic abnormalities. Several genes expected to be downregulated under RA deficiency appeared in the transcriptome data (e.g. Emx2, Foxg1 anteriorly, Cdx1, Hoxa1, Rarb posteriorly), whereas reverse-transcriptase-PCR and in situ hybridization performed for additional selected genes validated the changes identified through microarray analysis. Altogether, the affected genes belonged to numerous molecular pathways and cellular/organismal functions, demonstrating the pleiotropic nature of RA-dependent events. In both tissue samples, genes upregulated were more numerous than those downregulated, probably due to feedback regulatory loops. Bioinformatic analyses highlighted groups (clusters) of genes displaying similar behaviors in mutant tissues, and biological functions most significantly affected (e.g. mTOR, VEGF, ILK signaling in forebrain tissues; pyrimidine and purine metabolism, calcium signaling, one carbon metabolism in posterior tissues). Overall, these data give an overview of the gene expression changes resulting from embryonic RA deficiency, and provide new candidate genes and pathways that may help understanding retinoid-dependent molecular events.

Vitamin A and retinoid signaling: genomic and nongenomic effects

Vitamin A or retinol is arguably the most multifunctional vitamin in the human body, as it is essential from embryogenesis to adulthood. The pleiotropic effects of vitamin A are exerted mainly by one active metabolite, all-trans retinoic acid (atRA), which regulates the expression of a battery of target genes through several families of nuclear receptors (RARs, RXRs, and PPARβ/δ), polymorphic retinoic acid (RA) response elements, and multiple coregulators. It also involves extranuclear and nontranscriptional effects, such as the activation of kinase cascades, which are integrated in the nucleus via the phosphorylation of several actors of RA signaling. However, vitamin A itself proved recently to be active and RARs to be present in the cytosol to regulate translation and cell plasticity. These new concepts expand the scope of the biologic functions of vitamin A and RA.

Retinoids and nuclear retinoid receptors in white and brown adipose tissues: physiopathologic aspects

Vitamin A, ingested either as retinol or β-carotene from animal- or plant-derived foods respectively, is a nutrient essential for many biological functions such as embryonic development, vision, immune response, tissue remodeling, and metabolism. Its main active metabolite is all

Liver retinol transporter and receptor for serum retinol-binding protein (RBP4)

Vitamin A (retinol) is absorbed in the small intestine, stored in liver, and secreted into circulation bound to serum retinol-binding protein (RBP4). Circulating retinol may be taken up by extrahepatic tissues or recycled back to liver multiple times before it is finally metabolized or degraded. Liver exhibits high affinity binding sites for RBP4, but specific receptors have not been identified. The only known high affinity receptor for RBP4, Stra6, is not expressed in the liver. Here we report discovery of RBP4 receptor-2 (RBPR2), a novel retinol transporter expressed primarily in liver and intestine and induced in adipose tissue of obese mice. RBPR2 is structurally related to Stra6 and highly conserved in vertebrates, including humans. Expression of RBPR2 in cultured cells confers high affinity RBP4 binding and retinol transport, and RBPR2 knockdown reduces RBP4 binding/retinol transport. RBPR2 expression is suppressed by retinol and retinoic acid and correlates inversely with liver retinol stores in vivo. We conclude that RBPR2 is a novel retinol transporter that potentially regulates retinol homeostasis in liver and other tissues. In addition, expression of RBPR2 in liver and fat suggests a possible role in mediating established metabolic actions of RBP4 in those tissues.

Vitamin A deficiency induces congenital spinal deformities in rats

Most cases of congenital spinal deformities were sporadic and without strong evidence of heritability. The etiology of congenital spinal deformities is still elusive and assumed to be multi-factorial. The current study seeks to elucidate the effect of maternal vitamin A deficiency and the production of congenital spinal deformities in the offsping. Thirty two female rats were randomized into two groups: control group, which was fed a normal diet; vitamin A deficient group, which were given vitamin A-deficient diet from at least 2 weeks before mating till delivery. Three random neonatal rats from each group were killed the next day of parturition. Female rats were fed an AIN-93G diet sufficient in vitamin A to feed the rest of neonates for two weeks until euthanasia. Serum levels of vitamin A were assessed in the adult and filial rats. Anteroposterior (AP) spine radiographs were obtained at week 2 after delivery to evaluate the presence of the skeletal abnormalities especially of spinal deformities. Liver and vertebral body expression of retinaldehyde dehydrogenase (RALDHs) and RARs mRNA was assessed by reverse transcription-real time PCR. VAD neonates displayed many skeletal malformations in the cervical, thoracic, the pelvic and sacral and limbs regions. The incidence of congenital scoliosis was 13.79% (8/58) in the filial rats of vitamin A deficiency group and 0% in the control group. Furthermore, vitamin A deficiency negatively regulate the liver and verterbral body mRNA levels of RALDH1, RALDH2, RALDH3, RAR-α, RAR-β and RAR-γ. Vitamin A deficiency in pregnancy may induce congenital spinal deformities in the postnatal rats. The decreases of RALDHs and RARs mRNA expression induced by vitamin A deprivation suggest that vertebral birth defects may be caused by a defect in RA signaling pathway during somitogenesis.

DREM 2.0: Improved reconstruction of dynamic regulatory networks from time-series expression data

Background

Modeling dynamic regulatory networks is a major challenge since much of the protein-DNA interaction data available is static. The Dynamic Regulatory Events Miner (DREM) uses a Hidden Markov Model-based approach to integrate this static interaction data with time series gene expression leading to models that can determine when transcription factors (TFs) activate genes and what genes they regulate. DREM has been used successfully in diverse areas of biological research. However, several issues were not addressed by the original version.

Results

DREM 2.0 is a comprehensive software for reconstructing dynamic regulatory networks that supports interactive graphical or batch mode. With version 2.0 a set of new features that are unique in comparison with other softwares are introduced. First, we provide static interaction data for additional species. Second, DREM 2.0 now accepts continuous binding values and we added a new method to utilize TF expression levels when searching for dynamic models. Third, we added support for discriminative motif discovery, which is particularly powerful for species with limited experimental interaction data. Finally, we improved the visualization to support the new features. Combined, these changes improve the ability of DREM 2.0 to accurately recover dynamic regulatory networks and make it much easier to use it for analyzing such networks in several species with varying degrees of interaction information.

Conclusions

DREM 2.0 provides a unique framework for constructing and visualizing dynamic regulatory networks. DREM 2.0 can be downloaded from: www.sb.cs.cmu.edu/drem.

Studying and modelling dynamic biological processes using time-series gene expression data

Biological processes are often dynamic, thus researchers must monitor their activity at multiple time points. The most abundant source of information regarding such dynamic activity is time-series gene expression data. These data are used to identify the complete set of activated genes in a biological process, to infer their rates of change, their order and their causal effects and to model dynamic systems in the cell. In this Review we discuss the basic patterns that have been observed in time-series experiments, how these patterns are combined to form expression programs, and the computational analysis, visualization and integration of these data to infer models of dynamic biological systems.

POLYPHEMUS: R package for comparative analysis of RNA polymerase II ChIP-seq profiles by non-linear normalization

Chromatin immunoprecipitation coupled with massive parallel sequencing (ChIP-seq) is increasingly used to map protein–chromatin interactions at global scale. The comparison of ChIP-seq profiles for RNA polymerase II (PolII) established in different biological contexts, such as specific developmental stages or specific time-points during cell differentiation, provides not only information about the presence/accumulation of PolII at transcription start sites (TSSs) but also about functional features of transcription, including PolII stalling, pausing and transcript elongation. However, annotation and normalization tools for comparative studies of multiple samples are currently missing. Here, we describe the R-package POLYPHEMUS, which integrates TSS annotation with PolII enrichment over TSSs and coding regions, and normalizes signal intensity profiles. Thereby POLYPHEMUS facilitates to extract information about global PolII action to reveal changes in the functional state of genes. We validated POLYPHEMUS using a kinetic study on retinoic acid-induced differentiation and a publicly available data set from a comparative PolII ChIP-seq profiling in Caenorhabditis elegans. We demonstrate that POLYPHEMUS corrects the data sets by normalizing for technical variation between samples and reveal the potential of the algorithm in comparing multiple data sets to infer features of transcription regulation from dynamic PolII binding profiles.