Toucan: deciphering the cis-regulatory logic of coregulated genes

Rhizobium etli CFN42 proteomes showed isoenzymes in free-living and symbiosis with a different transcriptional regulation inferred from a transcriptional regulatory network

A comparative proteomic study at 6 h of growth in minimal medium (MM) and bacteroids at 18 days of symbiosis of Rhizobium etli CFN42 with the Phaseolus vulgaris leguminous plant was performed. A gene ontology classification of proteins in MM and bacteroid, showed 31 and 10 pathways with higher or equal than 30 and 20% of proteins with respect to genome content per pathway, respectively. These pathways were for energy and environmental compound metabolism, contributing to understand how Rhizobium is adapted to the different conditions. Metabolic maps based on orthology of the protein profiles, showed 101 and 74 functional homologous proteins in the MM and bacteroid profiles, respectively, which were grouped in 34 different isoenzymes showing a great impact in metabolism by covering 60 metabolic pathways in MM and symbiosis. Taking advantage of co-expression of transcriptional regulators (TF’s) in the profiles, by selection of genes whose matrices were clustered with matrices of TF’s, Transcriptional Regulatory networks (TRN´s) were deduced by the first time for these metabolic stages. In these clustered TF-MM and clustered TF-bacteroid networks, containing 654 and 246 proteins, including 93 and 46 TFs, respectively, showing valuable information of the TF’s and their regulated genes with high stringency. Isoenzymes were specific for adaptation to the different conditions and a different transcriptional regulation for MM and bacteroid was deduced. The parameters of the TRNs of these expected biological networks and biological networks of E. coli and B. subtilis segregate from the random theoretical networks. These are useful data to design experiments on TF gene–target relationships for bases to construct a TRN.

Identification of upstream transcription factor binding sites in orthologous genes using mixed Student’s t-test statistics

Background

Transcription factor (TF) regulates the transcription of DNA to messenger RNA by binding to upstream sequence motifs. Identifying the locations of known motifs in whole genomes is computationally intensive.

Methodology/Principal findings

This study presents a computational tool, named “Grit”, for screening TF-binding sites (TFBS) by coordinating transcription factors to their promoter sequences in orthologous genes. This tool employs a newly developed mixed Student’s t-test statistical method that detects high-scoring binding sites utilizing conservation information among species. The program performs sequence scanning at a rate of 3.2 Mbp/s on a quad-core Amazon server and has been benchmarked by the well-established ChIP-Seq datasets, putting Grit amongst the top-ranked TFBS predictors. It significantly outperforms the well-known transcription factor motif scanning tools, Pscan (4.8%) and FIMO (17.8%), in analyzing well-documented ChIP-Atlas human genome Chip-Seq datasets.

Significance

Grit is a good alternative to current available motif scanning tools.

Locating transcription factor-binding (TF-binding) site in the genome and identification their function is fundamental in understanding various biological processes. Improve the performance of the prediction tools is important because accurate TF-binding site prediction can save cost and time for wet-lab experiments. Also, genome wide TF-binding site prediction can provide new insights for transcriptome regulation in system biology perspective. This study developed a new TF-binding site prediction tool based on mixed Student’s t-test statistical method. The tool is amongst the top-ranked TF-binding site predictors, as such, it can help the researchers in TF-binding site identification and transcriptional regulation mechanism interpretation of genes.

Competitive dCas9 binding as a mechanism for transcriptional control

Catalytically dead Cas9 (dCas9) is a programmable transcription factor that can be targeted to promoters through the design of small guide RNAs (sgRNAs), where it can function as an activator or repressor. Natural promoters use overlapping binding sites as a mechanism for signal integration, where the binding of one can block, displace, or augment the activity of the other. Here, we implemented this strategy in Escherichia coli using pairs of sgRNAs designed to repress and then derepress transcription through competitive binding. When designed to target a promoter, this led to 27-fold repression and complete derepression. This system was also capable of ratiometric input comparison over two orders of magnitude. Additionally, we used this mechanism for promoter sequence-independent control by adopting it for elongation control, achieving 8-fold repression and 4-fold derepression. This work demonstrates a new genetic control mechanism that could be used to build analog circuit or implement cis-regulatory logic on CRISPRi-targeted native genes.

An in vivo functional genomics screen of nuclear receptors and their co-regulators identifies FOXA1 as an essential gene in lung tumorigenesis

Using a mini-library of 1062 lentiviral shRNAs targeting 40 nuclear hormone receptors and 70 of their co-regulators, we searched for potential therapeutic targets that would be important during in vivo tumor growth using a parallel in vitro and in vivo shRNA screening strategy in the non-small cell lung cancer (NSCLC) line NCI-H1819. We identified 21 genes essential for in vitro growth, and nine genes specifically required for tumor survival in vivo, but not in vitro: NCOR2, FOXA1, HDAC1, RXRA, RORB, RARB, MTA2, ETV4, and NR1H2. We focused on FOXA1, since it lies within the most frequently amplified genomic region in lung adenocarcinomas. We found that 14q-amplification in NSCLC cell lines was a biomarker for FOXA1 dependency for both in vivo xenograft growth and colony formation, but not mass culture growth in vitro. FOXA1 knockdown identified genes involved in electron transport among the most differentially regulated, indicating FOXA1 loss may lead to a decrease in cellular respiration. In support of this, FOXA1 amplification was correlated with increased sensitivity to the complex I inhibitor phenformin. Integrative ChipSeq analyses reveal that FOXA1 functions in this genetic context may be at least partially independent of NKX2-1. Our findings are consistent with a neomorphic function for amplified FOXA1, driving an oncogenic transcriptional program. These data provide new insight into the functional consequences of FOXA1 amplification in lung adenocarcinomas, and identify new transcriptional networks for exploration of therapeutic vulnerabilities in this patient population.

PLA2G4E, a candidate gene for resilience in Alzheimer´s disease and a new target for dementia treatment

Clinical studies revealed that some aged-individuals accumulate a significant number of histopathological Alzheimer´s disease (AD) lesions in their brain, yet without developing any signs of dementia. Animal models of AD represent suitable tools to identify genes that might promote cognitive resilience and hence, this study first set out to identify cognitively resilient individuals in the aged-Tg2576 mouse model. A transcriptomic analysis of these mice identified PLA2G4E as a gene that might confer resistance to dementia. Indeed, a significant decrease in PLA2G4E is evident in the brain of late-stage AD patients, whereas no such changes are observed in early stage patients with AD neuropathological lesions but no signs of dementia. We demonstrated that adeno-associated viral vector-mediated overexpression of PLA2G4E in hippocampal neurons completely restored cognitive deficits in elderly APP/PS1 mice, without affecting the amyloid or tau pathology. These PLA2G4E overexpressing APP/PS1 mice developed significantly more dendritic spines than sham-injected mice, coinciding with the cognitive improvement observed. Hence, these results support the idea that a loss of PLA2G4E might play a key role in the onset of dementia in AD, highlighting the potential of PLA2G4E overexpression as a novel therapeutic strategy to manage AD and other disorders that course with memory deficits.

cisTopic: cis-regulatory topic modeling on single-cell ATAC-seq data

We present cisTopic, a probabilistic framework used to simultaneously discover coaccessible enhancers and stable cell states from sparse single-cell epigenomics data ( http://github.com/aertslab/cistopic ). Using a compendium of single-cell ATAC-seq datasets from differentiating hematopoietic cells, brain and transcription factor perturbations, we demonstrate that topic modeling can be exploited for robust identification of cell types, enhancers and relevant transcription factors. cisTopic provides insight into the mechanisms underlying regulatory heterogeneity in cell populations.

Computational Approaches for Mining GRO-Seq Data to Identify and Characterize Active Enhancers

Transcriptional enhancers are DNA regulatory elements that are bound by transcription factors and act to positively regulate the expression of nearby or distally located target genes. Enhancers have many features that have been discovered using genomic analyses. Recent studies have shown that active enhancers recruit RNA polymerase II (Pol II) and are transcribed, producing enhancer RNAs (eRNAs). GRO-seq, a method for identifying the location and orientation of all actively transcribing RNA polymerases across the genome, is a powerful approach for monitoring nascent enhancer transcription. Furthermore, the unique pattern of enhancer transcription can be used to identify enhancers in the absence of any information about the underlying transcription factors. Here, we describe the computational approaches required to identify and analyze active enhancers using GRO-seq data, including data pre-processing, alignment, and transcript calling. In addition, we describe protocols and computational pipelines for mining GRO-seq data to identify active enhancers, as well as known transcription factor binding sites that are transcribed. Furthermore, we discuss approaches for integrating GRO-seq-based enhancer data with other genomic data, including target gene expression and function. Finally, we describe molecular biology assays that can be used to confirm and explore further the function of enhancers that have been identified using genomic assays. Together, these approaches should allow the user to identify and explore the features and biological functions of new cell type-specific enhancers.

An Empirical Prior Improves Accuracy for Bayesian Estimation of Transcription Factor Binding Site Frequencies within Gene Promoters

A Bayesian method for sampling from the distribution of matches to a precompiled transcription factor binding site (TFBS) sequence pattern (conditioned on an observed nucleotide sequence and the sequence pattern) is described. The method takes a position frequency matrix as input for a set of representative binding sites for a transcription factor and two sets of noncoding, 5′ regulatory sequences for gene sets that are to be compared. An empirical prior on the frequency A (per base pair of gene-vicinal, noncoding DNA) of TFBSs is developed using data from the ENCODE project and incorporated into the method. In addition, a probabilistic model for binding site occurrences conditioned on λ is developed analytically, taking into account the finite-width effects of binding sites. The count of TFBS β (conditioned on the observed sequence) is sampled using Metropolis–Hastings with an information entropy-based move generator. The derivation of the method is presented in a step-by-step fashion, starting from specific conditional independence assumptions. Empirical results show that the newly proposed prior on β improves accuracy for estimating the number of TFBS within a set of promoter sequences.

Drought response transcriptomes are altered in poplar with reduced tonoplast sucrose transporter expression

Transgenic Populus tremula x alba (717-1B4) plants with reduced expression of a tonoplast sucrose efflux transporter, PtaSUT4, exhibit reduced shoot growth compared to wild type (WT) under sustained mild drought. The present study was undertaken to determine whether SUT4-RNAi directly or indirectly altered poplar predisposition and/or response to changes in soil water availability. While sucrose and hexose levels were constitutively elevated in shoot organs, expression responses to drought were most altered in the root tips of SUT4-RNAi plants. Prior to any drought treatment, constitutively elevated transcript levels of abscisic acid biosynthetic genes and bark/vegetative storage proteins suggested altered metabolism in root tips of RNAi plants. Stronger drought-stimulation of stress-inducible genes encoding late-embryogenesis-abundant proteins in transgenic roots was consistent with increased vulnerability to soil drying. Transcript evidence suggested an RNAi effect on intercellular water trafficking by aquaporins in stem xylem during soil drying and recovery. Co-expression network analysis predicted altered integration of abscisic acid sensing/signaling with ethylene and jasmonate sensing/signaling in RNAi compared to WT roots. The overall conclusion is that steepened shoot-root sugar gradient in RNAi plants increased sensitivity of root tips to decreasing soil water availability.

Effect of single post-ovulatory administration of mifepristone (RU486) on transcript profile during the receptive period in human endometrium

Progesterone regulates uterine function during the luteal phase and is essential for the acquisition of endometrial receptivity. The objective of the present study was to identify endometrial transcripts whose expression is altered during the window of implantation after the administration of 200 mg of the antiprogestin mifepristone, 48 h after the LH peak (LH+2, LH+0=LH peak), and to determine the relationship of these transcripts with those regulated during the acquisition of receptivity. Endometrial samples were obtained in LH+7 from seven women of proven fertility, each one contributing with one cycle treated with placebo and another with mifepristone. Additionally, endometrial samples were obtained in LH+2 and LH+7 during a single untreated spontaneous cycle from seven normal fertile women as a reference. DNA microarrays were used to identify transcripts significantly regulated (defined as ≥2.0-fold change with false discovery rate below 1% usingt-test) with the administration of mifepristone vs placebo, or during the transition from pre-receptive to receptive (LH+2 vs LH+7). Approximately 2000 transcripts were significantly regulated in both comparisons (mifepristone vs placebo and LH+2 vs LH+7), but only 777 of them were coincident and displayed opposite regulation except for 25. The mRNA level for eight selected genes regulated by mifepristone was confirmed by real-time RT-PCR. We conclude that not all changes in endometrial transcript levels occurring in the transition from LH+2 to LH+7 seem to be regulated by the progesterone receptor and ∼37% of the genes whose transcript levels changed by effect of mifepristone could be associated with the acquisition of receptivity.

Systems Vaccinology: Applications, Trends, and Perspectives

The strategies employed in vaccinology have improved since the seminal work of Edward Jenner in the eighteenth century. Stimulated by failure to develop vaccines for cancers and chronic infectious diseases as well as an emergence of a multitude of new technologies not available earlier, vaccinology has moved from a largely experimental art to a new phase of innovation. Currently, immune reactions can be predicted and modeled before they occur and formulations can be optimized in advance for genetic background, age, sex, lifestyle, environmental factors, and microbiome. A multitude of scientific insights and technological advancements have led us to this current status, yet possibly none of the recent developments is individually more promising to achieve these goals than the interdisciplinary science of systems vaccinology. This review summarizes current trends and applications of systems vaccinology, including technically tangible areas of vaccine and immunology research which allow the transformative process into a truly broad understanding of vaccines, thereby effectively modeling interaction of vaccines with health and disease. It is becoming clear that a multitude of factors have to be considered to understand inter-patient variability of vaccine responses including those characterized from the interfaces between the immune system, microbiome, metabolome, and the nervous system.

NF-κB and IRF pathways: cross-regulation on target genes promoter level

Background

The NF-κB and IRF transcription factor families are major players in inflammation and antiviral response and act as two major effectors of the innate immune response (IIR). The regulatory mechanisms of activation of these two pathways and their interactions during the IIR are only partially known.

Results

Our in silico findings report that there is cross-regulation between both pathways at the level of gene transcription regulation, mediated by the presence of binding sites for both factors in promoters of genes essential for these pathways. These findings agree with recent experimental data reporting crosstalk between pathways activated by RIG-I and TLR3 receptors in response to pathogens.

Conclusions

We present an extended crosstalk diagram of the IRF - NF-κB pathways. We conclude that members of the NF-κB family may directly impact regulation of IRF family, while IRF members impact regulation of NF-κB family rather indirectly, via other transcription factors such as AP-1 and SP1.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1511-7) contains supplementary material, which is available to authorized users.

Summarizing and exploring data of a decade of cytokinin-related transcriptomics

The genome-wide transcriptional response of the model organism Arabidopsis thaliana to cytokinin has been investigated by different research groups as soon as large-scale transcriptomic techniques became affordable. Over the last 10 years many transcriptomic datasets related to cytokinin have been generated using different technological platforms, some of which are published only in databases, culminating in an RNA sequencing experiment. Two approaches have been made to establish a core set of cytokinin-regulated transcripts by meta-analysis of these datasets using different preferences regarding their selection. Here we add another meta-analysis derived from an independent microarray platform (CATMA), combine all the meta-analyses available with RNAseq data in order to establish an advanced core set of cytokinin-regulated transcripts, and compare the results with the regulation of orthologous rice genes by cytokinin. We discuss the functions of some of the less known cytokinin-regulated genes indicating areas deserving further research to explore cytokinin function. Finally, we investigate the promoters of the core set of cytokinin-induced genes for the abundance and distribution of known cytokinin-responsive cis elements and identify a set of novel candidate motifs.

An integrated functional genomic analysis identifies the antitumorigenic mechanism of action for PPARγ in lung cancer cells

Integrating the analysis of the cistrome of a transcription factor by ChIP-Seq with the study of its transcriptional output by microarray or RNA-Seq analysis is a powerful approach to elucidate the genomic functions of a transcription factor. Recently, we employed this approach to determine the mechanism of action by which the nuclear receptor PPARγ elicits its antitumorigenic effects in lung cancer cells upon activation by TZDs (1). Here we describe in detail the design, contents and quality controls for the gene expression and cistrome analyses associated with our study published in Cell Metabolism in 2014.

Inhibition of cancer cell proliferation by PPARγ is mediated by a metabolic switch that increases reactive oxygen species levels

The nuclear receptor peroxisome-proliferation-activated receptor gamma (PPARγ), a transcriptional master regulator of glucose and lipid metabolism, inhibits the growth of several common cancers, including lung cancer. In this study, we show that the mechanism by which activation of PPARγ inhibits proliferation of lung cancer cells is based on metabolic changes. We found that treatment with the PPARγ agonist pioglitazone triggers a metabolic switch that inhibits pyruvate oxidation and reduces glutathione levels. These PPARγ-induced metabolic changes result in a marked increase of reactive oxygen species (ROS) levels that lead to rapid hypophosphorylation of retinoblastoma protein (RB) and cell-cycle arrest. The antiproliferative effect of PPARγ activation can be prevented by suppressing pyruvate dehydrogenase kinase 4 (PDK4) or β-oxidation of fatty acids in vitro and in vivo. Our proposed mechanism also suggests that metabolic changes can rapidly and directly inhibit cell-cycle progression of cancer cells by altering ROS levels.

Large-scale investigation of human TF-miRNA relations based on coexpression profiles

Noncoding, endogenous microRNAs (miRNAs) are fairly well known for regulating gene expression rather than protein coding. Dysregulation of miRNA gene, either upregulated or downregulated, may lead to severe diseases or oncogenesis, especially when the miRNA disorder involves significant bioreactions or pathways. Thus, how miRNA genes are transcriptionally regulated has been highlighted as well as target recognition in recent years. In this study, a large-scale investigation of novel cis- and trans-elements was undertaken to further determine TF-miRNA regulatory relations, which are necessary to unravel the transcriptional regulation of miRNA genes. Based on miRNA and annotated gene expression profiles, the term “coTFBS” was introduced to detect common transcription factors and the corresponding binding sites within the promoter regions of each miRNA and its coexpressed annotated genes. The computational pipeline was successfully established to filter redundancy due to short sequence motifs for TFBS pattern search. Eventually, we identified more convinced TF-miRNA regulatory relations for 225 human miRNAs. This valuable information is helpful in understanding miRNA functions and provides knowledge to evaluate the therapeutic potential in clinical research. Once most expression profiles of miRNAs in the latest database are completed, TF candidates of more miRNAs can be explored by this filtering approach in the future.

Evolutionary tinkering of the expression of PDF1s suggests their joint effect on zinc tolerance and the response to pathogen attack

Multigenic families of Plant Defensin type 1 (PDF1) have been described in several species, including the model plant Arabidopsis thaliana as well as zinc tolerant and hyperaccumulator A. halleri. In A. thaliana, PDF1 transcripts (AtPDF1) accumulate in response to pathogen attack following synergic activation of ethylene/jasmonate pathways. However, in A. halleri, PDF1 transcripts (AhPDF1) are constitutively highly accumulated. Through an evolutionary approach, we investigated the possibility of A. halleri or A. thaliana species specialization in different PDF1s in conveying zinc tolerance and/or the response to pathogen attack via activation of the jasmonate (JA) signaling pathway. The accumulation of each PDF1 from both A. halleri and A. thaliana was thus compared in response to zinc excess and MeJA application. In both species, PDF1 paralogues were barely or not at all responsive to zinc. However, regarding the PDF1 response to JA signaling activation, A. thaliana had a higher number of PDF1s responding to JA signaling activation. Remarkably, in A. thaliana, a slight but significant increase in zinc tolerance was correlated with activation of the JA signaling pathway. In addition, A. halleri was found to be more tolerant to the necrotrophic pathogen Botrytis cinerea than A. thaliana. Since PDF1s are known to be promiscuous antifungal proteins able to convey zinc tolerance, we propose, on the basis of the findings of this study, that high constitutive PDF1 transcript accumulation in A. halleri is a potential way to skip the JA signaling activation step required to increase the PDF1 transcript level in the A. thaliana model species. This could ultimately represent an adaptive evolutionary process that would promote a PDF1 joint effect on both zinc tolerance and the response to pathogens in the A. halleri extremophile species.

Landscape of transcriptional deregulations in the preeclamptic placenta

Preeclampsia is a pregnancy disease affecting 5 to 8% of pregnant women and a leading cause of both maternal and fetal mortality and morbidity. Because of a default in the process of implantation, the placenta of preeclamptic women undergoes insufficient vascularization. This results in placental ischemia, inflammation and subsequent release of placental debris and vasoactive factors in the maternal circulation causing a systemic endothelial activation. Several microarray studies have analyzed the transcriptome of the preeclamptic placentas to identify genes which could be involved in placental dysfunction. In this study, we compared the data from publicly available microarray analyses to obtain a consensus list of modified genes. This allowed to identify consistently modified genes in the preeclamptic placenta. Of these, 67 were up-regulated and 31 down-regulated. Assuming that changes in the transcription level of co-expressed genes may result from the coordinated action of a limited number of transcription factors, we looked for over-represented putative transcription factor binding sites in the promoters of these genes. Indeed, we found that the promoters of up-regulated genes are enriched in putative binding sites for NFkB, CREB, ANRT, REEB1, SP1, and AP-2. In the promoters of down-regulated genes, the most prevalent putative binding sites are those of MZF-1, NFYA, E2F1 and MEF2A. These transcriptions factors are known to regulate specific biological pathways such as cell responses to inflammation, hypoxia, DNA damage and proliferation. We discuss here the molecular mechanisms of action of these transcription factors and how they can be related to the placental dysfunction in the context of preeclampsia.

Using graph models to find transcription factor modules: the hitting set problem and an exact algorithm

: Systematically perturbing a cellular system and monitoring the effects of the perturbations on gene expression provide a powerful approach to study signal transduction in gene expression systems. A critical step of revealing a signal transduction pathway regulating gene expression is to identify transcription factors transmitting signals in the system. In this paper, we address the task of identifying modules of cooperative transcription factors based on results derived from systems-biology experiments at two levels: First, a graph algorithm is developed to identify a minimum set of co-operative TFs that covers the differentially expressed genes under each systematic perturbation. Second, using a clique-finding approach, modules of TFs that tend to consistently cooperate together under various perturbations are further identified. Our results indicate that this approach is capable of identifying many known TF modules based on the individual experiment; thus we provide a novel graph-based method of identifying context-specific and highly reused TF-modules.

Genetic architecture of gene expression in the chicken

Background

The annotation of many genomes is limited, with a large proportion of identified genes lacking functional assignments. The construction of gene co-expression networks is a powerful approach that presents a way of integrating information from diverse gene expression datasets into a unified analysis which allows inferences to be drawn about the role of previously uncharacterised genes. Using this approach, we generated a condition-free gene co-expression network for the chicken using data from 1,043 publically available Affymetrix GeneChip Chicken Genome Arrays. This data was generated from a diverse range of experiments, including different tissues and experimental conditions. Our aim was to identify gene co-expression modules and generate a tool to facilitate exploration of the functional chicken genome.

Results

Fifteen modules, containing between 24 and 473 genes, were identified in the condition-free network. Most of the modules showed strong functional enrichment for particular Gene Ontology categories. However, a few showed no enrichment. Transcription factor binding site enrichment was also noted.

Conclusions

We have demonstrated that this chicken gene co-expression network is a useful tool in gene function prediction and the identification of putative novel transcription factors and binding sites. This work highlights the relevance of this methodology for functional prediction in poorly annotated genomes such as the chicken.

Comparative motif discovery combined with comparative transcriptomics yields accurate targetome and enhancer predictions

The identification of transcription factor binding sites, enhancers, and transcriptional target genes often relies on the integration of gene expression profiling and computational cis-regulatory sequence analysis. Methods for the prediction of cis-regulatory elements can take advantage of comparative genomics to increase signal-to-noise levels. However, gene expression data are usually derived from only one species. Here we investigate tissue-specific cross-species gene expression profiling by high-throughput sequencing, combined with cross-species motif discovery. First, we compared different methods for expression level quantification and cross-species integration using Tag-seq data. Using the optimal pipeline, we derived a set of genes with conserved expression during retinal determination across Drosophila melanogaster, Drosophila yakuba, and Drosophila virilis. These genes are enriched for binding sites of eye-related transcription factors including the zinc-finger Glass, a master regulator of photoreceptor differentiation. Validation of predicted Glass targets using RNA-seq in homozygous glass mutants confirms that the majority of our predictions are expressed downstream from Glass. Finally, we tested nine candidate enhancers by in vivo reporter assays and found eight of them to drive GFP in the eye disc, of which seven colocalize with the Glass protein, namely, scrt, chp, dpr10, CG6329, retn, Lim3, and dmrt99B. In conclusion, we show for the first time the combined use of cross-species expression profiling with cross-species motif discovery as a method to define a core developmental program, and we augment the candidate Glass targetome from a single known target gene, lozenge, to at least 62 conserved transcriptional targets.

Regulation of alternative splicing by the circadian clock and food related cues

Background

The circadian clock orchestrates daily rhythms in metabolism, physiology and behaviour that allow organisms to anticipate regular changes in their environment, increasing their adaptation. Such circadian phenotypes are underpinned by daily rhythms in gene expression. Little is known, however, about the contribution of post-transcriptional processes, particularly alternative splicing.

Results

Using Affymetrix mouse exon-arrays, we identified exons with circadian alternative splicing in the liver. Validated circadian exons were regulated in a tissue-dependent manner and were present in genes with circadian transcript abundance. Furthermore, an analysis of circadian mutant Vipr2^-/- mice revealed the existence of distinct physiological pathways controlling circadian alternative splicing and RNA binding protein expression, with contrasting dependence on Vipr2-mediated physiological signals. This view was corroborated by the analysis of the effect of fasting on circadian alternative splicing. Feeding is an important circadian stimulus, and we found that fasting both modulates hepatic circadian alternative splicing in an exon-dependent manner and changes the temporal relationship with transcript-level expression.

Conclusions

The circadian clock regulates alternative splicing in a manner that is both tissue-dependent and concurrent with circadian transcript abundance. This adds a novel temporal dimension to the regulation of mammalian alternative splicing. Moreover, our results demonstrate that circadian alternative splicing is regulated by the interaction between distinct physiological cues, and illustrates the capability of single genes to integrate circadian signals at different levels of regulation.

Motif discovery and transcription factor binding sites before and after the next-generation sequencing era

Motif discovery has been one of the most widely studied problems in bioinformatics ever since genomic and protein sequences have been available. In particular, its application to the de novo prediction of putative over-represented transcription factor binding sites in nucleotide sequences has been, and still is, one of the most challenging flavors of the problem. Recently, novel experimental techniques like chromatin immunoprecipitation (ChIP) have been introduced, permitting the genome-wide identification of protein-DNA interactions. ChIP, applied to transcription factors and coupled with genome tiling arrays (ChIP on Chip) or next-generation sequencing technologies (ChIP-Seq) has opened new avenues in research, as well as posed new challenges to bioinformaticians developing algorithms and methods for motif discovery.

GPMiner: an integrated system for mining combinatorial cis-regulatory elements in mammalian gene group

Background

Sequence features in promoter regions are involved in regulating gene transcription initiation. Although numerous computational methods have been developed for predicting transcriptional start sites (TSSs) or transcription factor (TF) binding sites (TFBSs), they lack annotations for do not consider some important regulatory features such as CpG islands, tandem repeats, the TATA box, CCAAT box, GC box, over-represented oligonucleotides, DNA stability, and GC content. Additionally, the combinatorial interaction of TFs regulates the gene group that is associated with same expression pattern. To investigate gene transcriptional regulation, an integrated system that annotates regulatory features in a promoter sequence and detects co-regulation of TFs in a group of genes is needed.

Results

This work identifies TSSs and regulatory features in a promoter sequence, and recognizes co-occurrence of cis-regulatory elements in co-expressed genes using a novel system. Three well-known TSS prediction tools are incorporated with orthologous conserved features, such as CpG islands, nucleotide composition, over-represented hexamer nucleotides, and DNA stability, to construct the novel Gene Promoter Miner (GPMiner) using a support vector machine (SVM). According to five-fold cross-validation results, the predictive sensitivity and specificity are both roughly 80%. The proposed system allows users to input a group of gene names/symbols, enabling the co-occurrence of TFBSs to be determined. Additionally, an input sequence can also be analyzed for homogeneity of experimental mammalian promoter sequences, and conserved regulatory features between homologous promoters can be observed through cross-species analysis. After identifying promoter regions, regulatory features are visualized graphically to facilitate gene promoter observations.

Conclusions

The GPMiner, which has a user-friendly input/output interface, has numerous benefits in analyzing human and mouse promoters. The proposed system is freely available at http://GPMiner.mbc.nctu.edu.tw/.

FGF-2 regulates cell proliferation, migration, and angiogenesis through an NDY1/KDM2B-miR-101-EZH2 pathway

The histone H3K27 methyltransferase EZH2 plays an important role in oncogenesis, by mechanisms that are incompletely understood. Here, we show that the JmjC domain histone H3 demethylase NDY1 synergizes with EZH2 to silence the EZH2 inhibitor miR-101. NDY1 and EZH2 repress miR-101 by binding its promoter in concert, via a process triggered by upregulation of NDY1. Whereas EZH2 binding depends on NDY1, the latter binds independently of EZH2. However, both are required to repress transcription. NDY1 and EZH2 acting in concert upregulate EZH2 and stabilize the repression of miR-101 and its outcome. NDY1 is induced by FGF-2 via CREB phosphorylation and activation, downstream of DYRK1A, and mediates the FGF-2 and EZH2 effects on cell proliferation, migration, and angiogenesis. The FGF-2-NDY1/EZH2-miR-101-EZH2 axis described here was found to be active in bladder cancer. These data delineate an oncogenic pathway that functionally links FGF-2 with EZH2 via NDY1 and miR-101.

Finding Transcription Factor Binding Motifs for Coregulated Genes by Combining Sequence Overrepresentation with Cross-Species Conservation

Novel computational methods for finding transcription factor binding motifs have long been sought due to tedious work of experimentally identifying them. However, the current prevailing methods yield a large number of false positive predictions due to the short, variable nature of transcriptional factor binding sites (TFBSs). We proposed here a method that combines sequence overrepresentation and cross-species sequence conservation to detect TFBSs in upstream regions of a given set of coregulated genes. We applied the method to 35S. cerevisiaetranscriptional factors with known DNA binding motifs (with the support of orthologous sequences from genomes ofS. mikatae,S. bayanus, andS. paradoxus), and the proposed method outperformed the single-genome-based motif finding methodsMEMEandAlignACEas well as the multiple-genome-based methodsPHYMEandFootprinterfor the majority of these transcriptional factors. Compared with the prevailing motif finding software, our method has some advantages in finding transcriptional factor binding motifs for potential coregulated genes if the gene upstream sequences of multiple closely related species are available. Although we used yeast genomes to assess our method in this study, it might also be applied to other organisms if suitable related species are available and the upstream sequences of coregulated genes can be obtained for the multiple closely related species.

Computational strategies for the genome-wide identification of cis-regulatory elements and transcriptional targets

Transcription factors (TFs) are key proteins that decode the information in our genome to express a precise and unique set of proteins and RNA molecules in each cell type in our body. These factors play a pivotal role in all biological processes, including the determination of a cell's fate during development and the maintenance of a cell's physiological function. To achieve this, a TF binds to specific DNA sequences in the noncoding part of the genome, recruits chromatin modifiers and cofactors, and directs the transcription initiation rate of its "target genes." Therefore, a key challenge in deciphering a transcriptional switch is to identify the direct target genes of the master regulators that control the switch, the cis-regulatory elements implementing (auto-)regulatory loops, and the target genes of all the TFs in the downstream regulatory network. A better knowledge of a TF's targetome during specification and differentiation of a particular cell type will generate mechanistic insight into its developmental program. Here, I review computational strategies and methods to predict transcriptional targets by genome-wide searches for TF binding sites using position weight matrices, motif clusters, phylogenetic footprinting, chromatin binding and accessibility data, enhancer classification, motif enrichment, and gene expression signatures.

Tbx20 regulates a genetic program essential to adult mouse cardiomyocyte function

Human mutations in or variants of TBX20 are associated with congenital heart disease, cardiomyopathy, and arrhythmias. To investigate whether cardiac disease in patients with these conditions results from an embryonic or ongoing requirement for Tbx20 in myocardium, we ablated Tbx20 specifically in adult cardiomyocytes in mice. This ablation resulted in the onset of severe cardiomyopathy accompanied by arrhythmias, with death ensuing within 1 to 2 weeks of Tbx20 ablation. Accounting for this dramatic phenotype, we identified molecular signatures that posit Tbx20 as a central integrator of a genetic program that maintains cardiomyocyte function in the adult heart. Expression of a number of genes encoding critical transcription factors, ion channels, and cytoskeletal/myofibrillar proteins was downregulated consequent to loss of Tbx20. Genome-wide ChIP analysis of Tbx20-binding regions in the adult heart revealed that many of these genes were direct downstream targets of Tbx20 and uncovered a previously undescribed DNA-binding site for Tbx20. Bioinformatics and in vivo functional analyses revealed a cohort of transcription factors that, working with Tbx20, integrated multiple environmental signals to maintain ion channel gene expression in the adult heart. Our data provide insight into the mechanisms by which mutations in TBX20 cause adult heart disease in humans.

Molecular organization and phylogenetic analysis of 5S rDNA in crustaceans of the genus Pollicipes reveal birth-and-death evolution and strong purifying selection

BACKGROUND

The 5S ribosomal DNA (5S rDNA) is organized in tandem arrays with repeat units that consist of a transcribing region (5S) and a variable nontranscribed spacer (NTS), in higher eukaryotes. Until recently the 5S rDNA was thought to be subject to concerted evolution, however, in several taxa, sequence divergence levels between the 5S and the NTS were found higher than expected under this model. So, many studies have shown that birth-and-death processes and selection can drive the evolution of 5S rDNA. In analyses of 5S rDNA evolution is found several 5S rDNA types in the genome, with low levels of nucleotide variation in the 5S and a spacer region highly divergent. Molecular organization and nucleotide sequence of the 5S ribosomal DNA multigene family (5S rDNA) were investigated in three Pollicipes species in an evolutionary context.

RESULTS

The nucleotide sequence variation revealed that several 5S rDNA variants occur in Pollicipes genomes. They are clustered in up to seven different types based on differences in their nontranscribed spacers (NTS). Five different units of 5S rDNA were characterized in P. pollicipes and two different units in P. elegans and P. polymerus. Analysis of these sequences showed that identical types were shared among species and that two pseudogenes were present. We predicted the secondary structure and characterized the upstream and downstream conserved elements. Phylogenetic analysis showed an among-species clustering pattern of 5S rDNA types.

CONCLUSIONS

These results suggest that the evolution of Pollicipes 5S rDNA is driven by birth-and-death processes with strong purifying selection.

MotifClick: prediction of cis-regulatory binding sites via merging cliques

Background

Although dozens of algorithms and tools have been developed to find a set of cis-regulatory binding sites called a motif in a set of intergenic sequences using various approaches, most of these tools focus on identifying binding sites that are significantly different from their background sequences. However, some motifs may have a similar nucleotide distribution to that of their background sequences. Therefore, such binding sites can be missed by these tools.

Results

Here, we present a graph-based polynomial-time algorithm, MotifClick, for the prediction of cis-regulatory binding sites, in particular, those that have a similar nucleotide distribution to that of their background sequences. To find binding sites with length k, we construct a graph using some 2(k-1)-mers in the input sequences as the vertices, and connect two vertices by an edge if the maximum number of matches of the local gapless alignments between the two 2(k-1)-mers is greater than a cutoff value. We identify a motif as a set of similar k-mers from a merged group of maximum cliques associated with some vertices.

Conclusions

When evaluated on both synthetic and real datasets of prokaryotes and eukaryotes, MotifClick outperforms existing leading motif-finding tools for prediction accuracy and balancing the prediction sensitivity and specificity in general. In particular, when the distribution of nucleotides of binding sites is similar to that of their background sequences, MotifClick is more likely to identify the binding sites than the other tools.

Meta-analysis of high-throughput datasets reveals cellular responses following hemorrhagic fever virus infection

The continuing use of high-throughput assays to investigate cellular responses to infection is providing a large repository of information. Due to the large number of differentially expressed transcripts, often running into the thousands, the majority of these data have not been thoroughly investigated. Advances in techniques for the downstream analysis of high-throughput datasets are providing additional methods for the generation of additional hypotheses for further investigation. The large number of experimental observations, combined with databases that correlate particular genes and proteins with canonical pathways, functions and diseases, allows for the bioinformatic exploration of functional networks that may be implicated in replication or pathogenesis. Herein, we provide an example of how analysis of published high-throughput datasets of cellular responses to hemorrhagic fever virus infection can generate additional functional data. We describe enrichment of genes involved in metabolism, post-translational modification and cardiac damage; potential roles for specific transcription factors and a conserved involvement of a pathway based around cyclooxygenase-2. We believe that these types of analyses can provide virologists with additional hypotheses for continued investigation.

Effect of PITX2 knockdown on transcriptome of primary human trabecular meshwork cell cultures

PURPOSE

To identify genes whose expressions in primary human trabecular meshwork (TM) cell cultures are affected by the transcription factor pituitary homeobox 2 (PITX2) and to identify genes that may have roles in glaucoma. Known glaucoma causing genes account for disease in a small fraction of patients, and we aimed at identification of other genes that may have subtle and accumulative effects not easily identifiable by a genetic approach.

METHODS

Expression profiles derived using microarrays were compared between TM control cells and cells treated with PITX2 siRNAs using three protocols so as to minimize false positive and negative results. The first protocol was based on the commonly used B statistic. The second and third protocols were based on fold change in expression. The second protocol used a threshold of at least 2 fold change in expression, whereas the third protocol used ranking in fold change without setting a threshold. The likelihood of a selected gene being a true positive was considered to correlate with the number of protocols by which it was selected. By considering all genes that were selected by at least one protocol, the likelihood of false negatives was expected to decrease. Effects on a subset of selected genes were verified by real time PCR, western blots, and immunocytochemistry. Effects on ALDH1A1, were further pursued because its protein product, aldehyde dehydrogenase 1 family, member A1, has roles in oxidative stress and because oxidative stress is known to be relevant to the etiology of glaucoma.

RESULTS

The expression level of 41 genes was assessed by to be possibly affected by PITX2 knockdown. Twenty one genes were down-regulated and twenty were upregulated. The expression of five genes was assessed to be altered by all three analysis protocols. The five genes were DIRAS3 (DIRAS family, GTP-binding RAS-like 3), CXCL6 (chemokine (C-X-C motif) ligand 6), SAMD5 (sterile alpha motif domain containing 5), CBFB (core-binding factor, beta subunit), and MEIS2 (meis homeobox 2). Real time PCR experiments verified results on a subset of genes tested. Notably, the results were also confirmed in two independent TMs. Effects on CXCL6 and ALDH1A1 were also confirmed by western blots, and effects on ALDH1A1 were further shown by immunocytochemistry. Data consistent with PITX2 involvement in ALDH1A1 mediated response to oxidative stress were presented.

CONCLUSIONS

Bioinformatics tools revealed that the genes identified affect functions and pathways relevant to glaucoma. Involvement of PITX2 in expression of some of the genes and in some of the pathways is being reported here for the first time. As many of the genes identified have not been studied vis-à-vis glaucoma, we feel they introduce new candidates for understanding this devastating disease.

LLM3D: a log-linear modeling-based method to predict functional gene regulatory interactions from genome-wide expression data

All cellular processes are regulated by condition-specific and time-dependent interactions between transcription factors and their target genes. While in simple organisms, e.g. bacteria and yeast, a large amount of experimental data is available to support functional transcription regulatory interactions, in mammalian systems reconstruction of gene regulatory networks still heavily depends on the accurate prediction of transcription factor binding sites. Here, we present a new method, log-linear modeling of 3D contingency tables (LLM3D), to predict functional transcription factor binding sites. LLM3D combines gene expression data, gene ontology annotation and computationally predicted transcription factor binding sites in a single statistical analysis, and offers a methodological improvement over existing enrichment-based methods. We show that LLM3D successfully identifies novel transcriptional regulators of the yeast metabolic cycle, and correctly predicts key regulators of mouse embryonic stem cell self-renewal more accurately than existing enrichment-based methods. Moreover, in a clinically relevant in vivo injury model of mammalian neurons, LLM3D identified peroxisome proliferator-activated receptor γ (PPARγ) as a neuron-intrinsic transcriptional regulator of regenerative axon growth. In conclusion, LLM3D provides a significant improvement over existing methods in predicting functional transcription regulatory interactions in the absence of experimental transcription factor binding data.

Improved detection of motifs with preferential location in promoters

Many transcription factor binding sites (TFBSs) involved in gene expression regulation are preferentially located relative to the transcription start site. This property is exploited in in silico prediction approaches, one of which involves studying the local overrepresentation of motifs using a sliding window to scan promoters with considerable accuracy. Nevertheless, the consequences of the choice of the sliding window size have never before been analysed. We propose an automatic adaptation of this size to each motif distribution profile. This approach allows a better characterization of the topological constraints of the motifs and the lists of genes containing them. Moreover, our approach allowed us to highlight a nonconstant frequency of occurrence of spurious motifs that could be counter-selected close to their functional area. Therefore, to improve the accuracy of in silico prediction of TFBSs and the sensitivity of the promoter cartography, we propose, in addition to automatic adaptation of window size, consideration of the nonconstant frequency of motifs in promoters.

Bioinformatic detection of E47, E2F1 and SREBP1 transcription factors as potential regulators of genes associated to acquisition of endometrial receptivity

BACKGROUND

The endometrium is a dynamic tissue whose changes are driven by the ovarian steroidal hormones. Its main function is to provide an adequate substrate for embryo implantation. Using microarray technology, several reports have provided the gene expression patterns of human endometrial tissue during the window of implantation. However it is required that biological connections be made across these genomic datasets to take full advantage of them. The objective of this work was to perform a research synthesis of available gene expression profiles related to acquisition of endometrial receptivity for embryo implantation, in order to gain insights into its molecular basis and regulation.

METHODS

Gene expression datasets were intersected to determine a consensus endometrial receptivity transcript list (CERTL). For this cluster of genes we determined their functional annotations using available web-based databases. In addition, promoter sequences were analyzed to identify putative transcription factor binding sites using bioinformatics tools and determined over-represented features.

RESULTS

We found 40 up- and 21 down-regulated transcripts in the CERTL. Those more consistently increased were C4BPA, SPP1, APOD, CD55, CFD, CLDN4, DKK1, ID4, IL15 and MAP3K5 whereas the more consistently decreased were OLFM1, CCNB1, CRABP2, EDN3, FGFR1, MSX1 and MSX2. Functional annotation of CERTL showed it was enriched with transcripts related to the immune response, complement activation and cell cycle regulation. Promoter sequence analysis of genes revealed that DNA binding sites for E47, E2F1 and SREBP1 transcription factors were the most consistently over-represented and in both up- and down-regulated genes during the window of implantation.

CONCLUSIONS

Our research synthesis allowed organizing and mining high throughput data to explore endometrial receptivity and focus future research efforts on specific genes and pathways. The discovery of possible new transcription factors orchestrating the CERTL opens new alternatives for understanding gene expression regulation in uterine function.

Jarid2 is among a set of genes differentially regulated by Nkx2.5 during outflow tract morphogenesis

Nkx2.5, a transcription factor implicated in human congenital heart disease, is required for regulation of second heart field (SHF) progenitors contributing to outflow tract (OFT). Here, we define a set of genes (Lrrn1, Elovl2, Safb, Slc39a6, Khdrbs1, Hoxb4, Fez1, Ccdc117, Jarid2, Nrcam, and Enpp3) expressed in SHF containing pharyngeal arch tissue whose regulation is dependent on Nkx2.5. Further investigation shows that Jarid2, which has been implicated in OFT morphogenesis, is a direct target of Nkx2.5 regulation. Jarid2 expression was up-regulated in SHF mesoderm of Nkx2.5-deficient embryos. Chromatin immunoprecipitation analysis showed Nkx2.5 interaction with consensus binding sites in the Jarid2 promoter in pharyngeal arch cells. Finally, Jarid2 promoter activity and mRNA expression levels were down-regulated by Nkx2.5 overexpression. Given the role of Jarid2 as a regulator of early cardiac proliferation, these findings highlight Jarid2 as one of several potential mediators of the critical role played by Nkx2.5 during OFT morphogenesis.

Genome-wide profiling of p63 DNA-binding sites identifies an element that regulates gene expression during limb development in the 7q21 SHFM1 locus

Heterozygous mutations in p63 are associated with split hand/foot malformations (SHFM), orofacial clefting, and ectodermal abnormalities. Elucidation of the p63 gene network that includes target genes and regulatory elements may reveal new genes for other malformation disorders. We performed genome-wide DNA–binding profiling by chromatin immunoprecipitation (ChIP), followed by deep sequencing (ChIP–seq) in primary human keratinocytes, and identified potential target genes and regulatory elements controlled by p63. We show that p63 binds to an enhancer element in the SHFM1 locus on chromosome 7q and that this element controls expression of DLX6 and possibly DLX5, both of which are important for limb development. A unique micro-deletion including this enhancer element, but not the DLX5/DLX6 genes, was identified in a patient with SHFM. Our study strongly indicates disruption of a non-coding cis-regulatory element located more than 250 kb from the DLX5/DLX6 genes as a novel disease mechanism in SHFM1. These data provide a proof-of-concept that the catalogue of p63 binding sites identified in this study may be of relevance to the studies of SHFM and other congenital malformations that resemble the p63-associated phenotypes.

Mammalian embryonic development requires precise control of gene expression in the right place at the right time. One level of control of gene expression is through cis-regulatory elements controlled by transcription factors. Deregulation of gene expression by mutations in such cis-regulatory elements has been described in developmental disorders. Heterozygous mutations in the transcription factor p63 are found in patients with limb malformations, cleft lip/palate, and defects in skin and other epidermal appendages, through disruption of normal ectodermal development during embryogenesis. We reasoned that the identification of target genes and cis-regulatory elements controlled by p63 would provide candidate genes for defects arising from abnormally regulated ectodermal development. To test our hypothesis, we carried out a genome-wide binding site analysis and identified a large number of target genes and regulatory elements regulated by p63. We further showed that one of these regulatory elements controls expression of DLX6 and possibly DLX5 in the apical ectodermal ridge in the developing limbs. Loss of this element through a micro-deletion was associated with split hand foot malformation (SHFM1). The list of p63 binding sites provides a resource for the identification of mutations that cause ectodermal dysplasias and malformations in humans.

Regulator of calcineurin 1 controls growth plasticity of adult pancreas

BACKGROUND & AIMS

Growth of exocrine pancreas is regulated by gastrointestinal hormones, notably cholecystokinin (CCK). CCK-driven pancreatic growth requires calcineurin (CN), which activates Nuclear Factor of Activated T cells (NFATs), but the genetic underpinnings and feedback mechanisms that regulate this response are not known.

METHODS

Pancreatic growth was stimulated by protease inhibitor (PI)-containing chow, which induces secretion of endogenous CCK. Expression profiling of PI stimulation was performed on Affymetrix 430A chips, and CN was inhibited via FK506. Exocrine pancreas-specific overexpression of CN inhibitor Regulator of Calcineurin 1 (Rcan1) was achieved by breeding elastase-Cre(estrogen receptor [ER]) transgenics with "flox-on" Rcan1 mice.

RESULTS

CN inhibitor FK506 blocked expression of 38 genes, as confirmed by quantitative polymerase chain reaction. The CN-dependent genes were linked to growth-related processes, whereas their promoters were enriched in NFAT and NFAT/AP1 sites. Multiple NFAT targets, including Rcan1, Rgs2, HB-EGF, Lif, and Gem, were validated by chromatin immunoprecipitation. One of these, a CN feedback inhibitor Rcan1, was induced >50 fold during 1-8 hours course of pancreatic growth and strongly inhibited (>99%) by FK506. To examine its role in pancreatic growth, we overexpressed Rcan1 in an inducible, acinar-specific fashion. Rcan1 overexpression inhibited CN-NFAT signaling, as shown using an NFAT-luciferase reporter and quantitative polymerase chain reaction. Most importantly, the increase in exocrine pancreas size, protein/DNA content, and acinar proliferation were all blocked in Rcan1 overexpressing mice.

CONCLUSIONS

We profile adaptive pancreatic growth, identify Rcan1 as an important new feedback regulator, and firmly establish that CN-NFAT signaling is required for this response.

Robust target gene discovery through transcriptome perturbations and genome-wide enhancer predictions in Drosophila uncovers a regulatory basis for sensory specification

CisTarget X is a novel computational method that accurately predicts Atonal governed regulatory networks in the retina of the fruit fly.

A comprehensive systems-level understanding of developmental programs requires the mapping of the underlying gene regulatory networks. While significant progress has been made in mapping a few such networks, almost all gene regulatory networks underlying cell-fate specification remain unknown and their discovery is significantly hampered by the paucity of generalized, in vivo validated tools of target gene and functional enhancer discovery. We combined genetic transcriptome perturbations and comprehensive computational analyses to identify a large cohort of target genes of the proneural and tumor suppressor factor Atonal, which specifies the switch from undifferentiated pluripotent cells to R8 photoreceptor neurons during larval development. Extensive in vivo validations of the predicted targets for the proneural factor Atonal demonstrate a 50% success rate of bona fide targets. Furthermore we show that these enhancers are functionally conserved by cloning orthologous enhancers from Drosophila ananassae and D. virilis in D. melanogaster. Finally, to investigate cis-regulatory cross-talk between Ato and other retinal differentiation transcription factors (TFs), we performed motif analyses and independent target predictions for Eyeless, Senseless, Suppressor of Hairless, Rough, and Glass. Our analyses show that cisTargetX identifies the correct motif from a set of coexpressed genes and accurately predicts target genes of individual TFs. The validated set of novel Ato targets exhibit functional enrichment of signaling molecules and a subset is predicted to be coregulated by other TFs within the retinal gene regulatory network.

Tens of thousands of regulatory elements determine the spatiotemporal expression pattern of protein-coding genes in the metazoan genome. Each regulatory element, when bound by the appropriate transcription factors, can affect the temporal transcription of a nearby target gene in a particular cell type. Annotating the genome for regulatory elements, as well as determining the input transcription factors for each element, is a key challenge in genome biology. In this study, we introduce a computational method, cisTargetX, that predicts transcription factor binding motifs and their target genes through the integration of gene expression data and comparative genomics. We first validate this method in silico using public gene expression data and, then, apply cisTargetX to the developmental program governing photoreceptor neuron specification in the retina of Drosophila melanogaster. Particularly, we perturbed predicted key transcription factors during the initial steps of neurogenesis; measure gene expression by microarrays; identify motifs and predict target genes; validate the predictions in vivo using transgenic animals; and study several functional and evolutionary aspects of the validated regulatory elements for the proneural factor Atonal. Overall, we show that cisTargetX efficiently predicts genetic regulatory interactions and provides mechanistic insight into gene regulatory networks of postembryonic developmental systems.

Combinatorial binding leads to diverse regulatory responses: Lmd is a tissue-specific modulator of Mef2 activity

Understanding how complex patterns of temporal and spatial expression are regulated is central to deciphering genetic programs that drive development. Gene expression is initiated through the action of transcription factors and their cofactors converging on enhancer elements leading to a defined activity. Specific constellations of combinatorial occupancy are therefore often conceptualized as rigid binding codes that give rise to a common output of spatio-temporal expression. Here, we assessed this assumption using the regulatory input of two essential transcription factors within the Drosophila myogenic network. Mutations in either Myocyte enhancing factor 2 (Mef2) or the zinc-finger transcription factor lame duck (lmd) lead to very similar defects in myoblast fusion, yet the underlying molecular mechanism for this shared phenotype is not understood. Using a combination of ChIP-on-chip analysis and expression profiling of loss-of-function mutants, we obtained a global view of the regulatory input of both factors during development. The majority of Lmd-bound enhancers are co-bound by Mef2, representing a subset of Mef2's transcriptional input during these stages of development. Systematic analyses of the regulatory contribution of both factors demonstrate diverse regulatory roles, despite their co-occupancy of shared enhancer elements. These results indicate that Lmd is a tissue-specific modulator of Mef2 activity, acting as both a transcriptional activator and repressor, which has important implications for myogenesis. More generally, this study demonstrates considerable flexibility in the regulatory output of two factors, leading to additive, cooperative, and repressive modes of co-regulation.

While genetic studies are essential to reveal the phenotypic relationships between genes, it is often very difficult to disentangle the molecular mechanism of two genes that phenocopy each other. In this study, we used global scale and single gene analysis to investigate the relationship between two transcription factors whose mutant embryos have a similar defect in myogenesis. In Drosophila, Mef2 mutant embryos display a block in myoblast fusion, which is very similar to what is observed in mutant embryos for lmd, a zinc-finger transcription factor. To understand the underlying nature of these defects we used ChIP-on-chip analysis to obtain a global view of their co-regulated enhancers, and we used expression profiling of mutant embryos to reveal their downstream transcriptional response. The results indicate that Lmd acts as a tissue specific modulator of Mef2 activity. Using in vivo and in vitro reporter assays, we show that co-binding to the same enhancer element can lead to diverse regulatory responses. The presence of Lmd has an additive, cooperative, or repressive effect on Mef2 activity, demonstrating that it acts as a molecular switch for gene expression during muscle differentiation. More broadly, our results highlight the difficulty in translating information on combinatorial binding data into a functional regulatory response.

A computational evaluation of over-representation of regulatory motifs in the promoter regions of differentially expressed genes

Background

Observed co-expression of a group of genes is frequently attributed to co-regulation by shared transcription factors. This assumption has led to the hypothesis that promoters of co-expressed genes should share common regulatory motifs, which forms the basis for numerous computational tools that search for these motifs. While frequently explored for yeast, the validity of the underlying hypothesis has not been assessed systematically in mammals. This demonstrates the need for a systematic and quantitative evaluation to what degree co-expressed genes share over-represented motifs for mammals.

Results

We identified 33 experiments for human and mouse in the ArrayExpress Database where transcription factors were manipulated and which exhibited a significant number of differentially expressed genes. We checked for over-representation of transcription factor binding sites in up- or down-regulated genes using the over-representation analysis tool oPOSSUM. In 25 out of 33 experiments, this procedure identified the binding matrices of the affected transcription factors. We also carried out de novo prediction of regulatory motifs shared by differentially expressed genes. Again, the detected motifs shared significant similarity with the matrices of the affected transcription factors.

Conclusions

Our results support the claim that functional regulatory motifs are over-represented in sets of differentially expressed genes and that they can be detected with computational methods.

Molecular characterization of the Ggamma-globin-Tag transgenic mouse model of hormone refractory prostate cancer: comparison to human prostate cancer

BACKGROUND

Prostate cancer (PrCa) has a high incidence in Western countries and at present, there is no cure for hormone refractory prostate cancer. Transgenic mouse models have proven useful for understanding mechanisms of prostate carcinogenesis. The characterization of genetically modified mouse PrCa models using high-throughput genomic analyses provides important information to guide appropriate experiment applications for such model.

METHODS

We have analyzed the transcriptome of the hormone refractory and highly metastatic Fetal Globin-SV40/T-antigen (Ggamma-globin-Tag) transgenic mouse model for PrCa compared to normal mouse prostate tissue. Gene expression patterns found in Ggamma-globin-Tag mouse prostate tumors were compared with publicly available human localized and metastatic prostate tumors (GEO accession # GSE3325) through hierarchical cluster analysis, Pearson's rank correlation coefficient, and Self Organizing Feature Maps (SOM) analyses.

RESULTS

Ggamma-globin-Tag tumors clustered closely with human metastatic tumors and gene expression patterns had a significant correlation (P < 0.01), unlike human localized primary tumors (P > 0.6). Bioinformatic analyses identified deregulated genetic pathways and networks in Ggamma-globin-Tag tumors, which displayed similarities to alterations in human PrCa. Changes in the expression of genes involved in DNA replication and repair (Rb1, p53, Myc, PCNA, DNMT3A) and growth factor signaling pathways (TGFbeta2, ERK1/2, NRas, and Notch1) are deregulated in the Ggamma-globin-Tag tumors, suggesting their key role in the oncogenic process. Identification of an enrichment of putative binding sites for transcription factors revealed eight transcription factors that may be important in Ggamma-globin-Tag carcinogenesis, including SP1, NF-Y, CREB, Elk1, and E2F. Novel genes related to microtubule regulation were also identified in Ggamma-globin-Tag tumors as potentially important candidate targets for PrCa. Overexpression of stathmin-1, whose expression was increased in human metastatic prostate tumors, was validated in Ggamma-globin-Tag tumors by immunohistochemistry. This protein belongs to the SV40/T-antigen cancer signature identified in previous studies in prostate, breast, and lung cancer mouse models.

CONCLUSIONS

Our results show that the Ggamma-globin-Tag model for hormone refractory PrCa shares important features with aggressive, metastatic human PrCa. Given the role of stathmin-1 in the destabilization of microtubles and taxane resistance, the Ggamma-globin-Tag model and other SV40/T-antigen driven transgenic models may be useful for testing potential therapies directed at stathmin-1 in human prostate tumors.

HRE1 and HRE2, two hypoxia-inducible ethylene response factors, affect anaerobic responses in Arabidopsis thaliana

Plants often experience challenging hypoxic conditions imposed by soil waterlogging or complete flooding. In rice, Sub1A, a flooding-induced ethylene responsive factor (ERF) plays a crucial role in submergence tolerance. In this study, we examined two Arabidopsis Hypoxia Responsive ERF genes (HRE1 and HRE2), belonging to the same ERF group as Sub1A. Transgenic Arabidopsis plants, which over-expressed HRE1, showed an improved tolerance of anoxia, whereas a double-knockout mutant hre1hre2 was more susceptible than the wild type. HRE1 over-expressing plants showed an increased activity in the fermentative enzymes pyruvate decarboxylase and alcohol dehydrogenase together with increased ethanol production under hypoxia, but not in normoxia. Whole-genome microarray analyses suggested that an over-expression of HRE1, but not HRE2, increased the induction of most anaerobic genes under hypoxia. Real-time quantitative (q)PCR analyses confirmed a positive effect of HRE1 over-expression on several anaerobic genes, whereas the double-knockout mutant hre1hre2 showed a decreased expression in the same genes after 4 h of hypoxia. Single-knockout mutants did not show significant differences from the wild type. We found that the regulation of HRE1 and HRE2 by low oxygen relies on different mechanisms, since HRE1 requires protein synthesis to be induced while HRE2 does not. HRE2 is likely to be regulated post-transcriptionally by mRNA stabilization. We propose that HRE1 and HRE2 play a partially redundant role in low oxygen signalling in Arabidopsis thaliana, thus improving the tolerance of the plant to the stress by enhancing anaerobic gene expression and ethanolic fermentation.

Expression profiling after activation of amino acid deprivation response in HepG2 human hepatoma cells

Dietary protein malnutrition is manifested as amino acid deprivation of individual cells, which activates an amino acid response (AAR) that alters cellular functions, in part, by regulating transcriptional and posttranscriptional mechanisms. The AAR was activated in HepG2 human hepatoma cells, and the changes in mRNA content were analyzed by microarray expression profiling. The results documented that 1,507 genes were differentially regulated by P < 0.001 and by more than twofold in response to the AAR, 250 downregulated and 1,257 upregulated. The spectrum of altered genes reveals that amino acid deprivation has far-reaching implications for gene expression and cellular function. Among those cellular functions with the largest numbers of altered genes were cell growth and proliferation, cell cycle, gene expression, cell death, and development. Potential biological relationships between the differentially expressed genes were analyzed by computer software that generates gene networks. Proteins that were central to the most significant of these networks included c-myc, polycomb group proteins, transforming growth factor β1, nuclear factor (erythroid-derived 2)-like 2-related factor 2, FOS/JUN family members, and many members of the basic leucine zipper superfamily of transcription factors. Although most of these networks contained some genes that were known to be amino acid responsive, many new relationships were identified that underscored the broad impact that amino acid stress has on cellular function.

Genome-wide transcription factor binding site/promoter databases for the analysis of gene sets and co-occurrence of transcription factor binding motifs

Background

The use of global gene expression profiling is a well established approach to understand biological processes. One of the major goals of these investigations is to identify sets of genes with similar expression patterns. Such gene signatures may be very informative and reveal new aspects of particular biological processes. A logical and systematic next step is to reduce the identified gene signatures to the regulatory components that induce the relevant gene expression changes. A central issue in this context is to identify transcription factors, or transcription factor binding sites (TFBS), likely to be of importance for the expression of the gene signatures.

Results

We develop a strategy that efficiently produces TFBS/promoter databases based on user-defined criteria. The resulting databases constitute all genes in the Santa Cruz database and the positions for all TFBS provided by the user as position weight matrices. These databases are then used for two purposes, to identify significant TFBS in the promoters in sets of genes and to identify clusters of co-occurring TFBS. We use two criteria for significance, significantly enriched TFBS in terms of total number of binding sites for the promoters, and significantly present TFBS in terms of the fraction of promoters with binding sites. Significant TFBS are identified by a re-sampling procedure in which the query gene set is compared with typically 10⁵ gene lists of similar size randomly drawn from the TFBS/promoter database. We apply this strategy to a large number of published ChIP-Chip data sets and show that the proposed approach faithfully reproduces ChIP-Chip results. The strategy also identifies relevant TFBS when analyzing gene signatures obtained from the MSigDB database. In addition, we show that several TFBS are highly correlated and that co-occurring TFBS define functionally related sets of genes.

Conclusions

The presented approach of promoter analysis faithfully reproduces the results from several ChIP-Chip and MigDB derived gene sets and hence may prove to be an important method in the analysis of gene signatures obtained through ChIP-Chip or global gene expression experiments. We show that TFBS are organized in clusters of co-occurring TFBS that together define highly coherent sets of genes.

TaNF-YC11, one of the light-upregulated NF-YC members in Triticum aestivum, is co-regulated with photosynthesis-related genes

Nuclear factor Y (NF-Y) is a heterotrimeric transcription factor complex. Each of the NF-Y subunits (NF-YA, NF-YB and NF-YC) in plants is encoded by multiple genes. Quantitative RT-PCR analysis revealed that five wheat NF-YC members (TaNF-YC5, 8, 9, 11 and 12) were upregulated by light in both the leaf and seedling shoot. Co-expression analysis of Affymetrix wheat genome array datasets revealed that transcript levels of a large number of genes were consistently correlated with those of the TaNF-YC11 and TaNF-YC8 genes in three to four separate Affymetrix array datasets. TaNF-YC11-correlated transcripts were significantly enriched with the Gene Ontology term photosynthesis. Sequence analysis in the promoters of TaNF-YC11-correlated genes revealed the presence of putative NF-Y complex binding sites (CCAAT motifs). Quantitative RT-PCR analysis of a subset of potential TaNF-YC11 target genes showed that ten out of the 13 genes were also light-upregulated in both the leaf and seedling shoot and had significantly correlated expression profiles with TaNF-YC11. The potential target genes for TaNF-YC11 include subunit members from all four thylakoid membrane-bound complexes required for the conversion of solar energy into chemical energy and rate-limiting enzymes in the Calvin cycle. These data indicate that TaNF-YC11 is potentially involved in regulation of photosynthesis-related genes.

iMotifs: an integrated sequence motif visualization and analysis environment

MOTIVATION

Short sequence motifs are an important class of models in molecular biology, used most commonly for describing transcription factor binding site specificity patterns. High-throughput methods have been recently developed for detecting regulatory factor binding sites in vivo and in vitro and consequently high-quality binding site motif data are becoming available for increasing number of organisms and regulatory factors. Development of intuitive tools for the study of sequence motifs is therefore important. iMotifs is a graphical motif analysis environment that allows visualization of annotated sequence motifs and scored motif hits in sequences. It also offers motif inference with the sensitive NestedMICA algorithm, as well as overrepresentation and pairwise motif matching capabilities. All of the analysis functionality is provided without the need to convert between file formats or learn different command line interfaces. The application includes a bundled and graphically integrated version of the NestedMICA motif inference suite that has no outside dependencies. Problems associated with local deployment of software are therefore avoided.

AVAILABILITY

iMotifs is licensed with the GNU Lesser General Public License v2.0 (LGPL 2.0). The software and its source is available at http://wiki.github.com/mz2/imotifs and can be run on Mac OS X Leopard (Intel/PowerPC). We also provide a cross-platform (Linux, OS X, Windows) LGPL 2.0 licensed library libxms for the Perl, Ruby, R and Objective-C programming languages for input and output of XMS formatted annotated sequence motif set files.

CONTACT

matias.piipari@gmail.com; imotifs@googlegroups.com.

MINER: exploratory analysis of gene interaction networks by machine learning from expression data

Background

The reconstruction of gene regulatory networks from high-throughput "omics" data has become a major goal in the modelling of living systems. Numerous approaches have been proposed, most of which attempt only "one-shot" reconstruction of the whole network with no intervention from the user, or offer only simple correlation analysis to infer gene dependencies.

Results

We have developed MINER (Microarray Interactive Network Exploration and Representation), an application that combines multivariate non-linear tree learning of individual gene regulatory dependencies, visualisation of these dependencies as both trees and networks, and representation of known biological relationships based on common Gene Ontology annotations. MINER allows biologists to explore the dependencies influencing the expression of individual genes in a gene expression data set in the form of decision, model or regression trees, using their domain knowledge to guide the exploration and formulate hypotheses. Multiple trees can then be summarised in the form of a gene network diagram. MINER is being adopted by several of our collaborators and has already led to the discovery of a new significant regulatory relationship with subsequent experimental validation.

Conclusion

Unlike most gene regulatory network inference methods, MINER allows the user to start from genes of interest and build the network gene-by-gene, incorporating domain expertise in the process. This approach has been used successfully with RNA microarray data but is applicable to other quantitative data produced by high-throughput technologies such as proteomics and "next generation" DNA sequencing.