TRANSFAC: an integrated system for gene expression regulation

Searching ChIP-seq genomic islands for combinatorial regulatory codes in mouse embryonic stem cells

Background

To facilitate deciphering underlying transcriptional regulatory circuits in mouse embryonic stem (ES) cells, recent ChIP-seq data provided genome-wide binding locations of several key transcription factors (TFs); meanwhile, existing efforts profiled gene expression in ES cells and in their early differentiated state. It has been shown that the gene expression profiles are correlated with the binding of these TFs. However, it remains unclear whether other TFs, referred to as cofactors, participate the gene regulation by collaborating with the ChIP-seq TFs.

Results

Based on our analyses of the ES gene expression profiles and binding sites of potential cofactors in vicinity of the ChIP-seq TF binding locations, we identified a list of co-binding features that show significantly different characteristics between different gene expression patterns (activated or repressed gene expression in ES cells) at a false discovery rate of 10%. Gene classification with a subset of the identified features achieved up to 20% improvement over classification only based on the ChIP-seq TFs. More than 1/3 of reasoned regulatory roles of cofactor candidates involved in these features are supported by existing literatures. Finally, the predicted target genes of the majority candidates present expected expression change in another independent data set, which serves as a supplementary validation of these candidates.

Conclusions

Our results revealed a list of combinatorial genomic features that are significantly associated with gene expression in ES cells, suggesting potential cofactors of the ChIP-seq TFs for gene regulation.

Endogenous myoglobin in breast cancer is hypoxia-inducible by alternative transcription and functions to impair mitochondrial activity: a role in tumor suppression?

Recently, immunohistochemical analysis of myoglobin (MB) in human breast cancer specimens has revealed a surprisingly widespread expression of MB in this nonmuscle context. The positive correlation with hypoxia-inducible factor 2α (HIF-2α) and carbonic anhydrase IX suggested that oxygen regulates myoglobin expression in breast carcinomas. Here, we report that MB mRNA and protein levels are robustly induced by prolonged hypoxia in breast cancer cell lines, in part via HIF-1/2-dependent transactivation. The hypoxia-induced MB mRNA originated from a novel alternative transcription start site 6 kb upstream of the ATG codon. MB regulation in normal and tumor tissue may thus be fundamentally different. Functionally, the knockdown of MB in MDA-MB468 breast cancer cells resulted in an unexpected increase of O(2) uptake and elevated activities of mitochondrial enzymes during hypoxia. Silencing of MB transcription attenuated proliferation rates and motility capacities of hypoxic cancer cells and, surprisingly, also fully oxygenated breast cancer cells. Endogenous MB in cancer cells is apparently involved in controlling oxidative cell energy metabolism, contrary to earlier findings on mouse heart, where the targeted disruption of the Mb gene did not effect myocardial energetics and O(2) consumption. This control function of MB seemingly impacts mitochondria and influences cell proliferation and motility, but it does so in ways not directly related to the facilitated diffusion or storage of O(2). Hypothetically, the mitochondrion-impairing role of MB in hypoxic cancer cells is part of a novel tumor-suppressive function.

A variant in the heart-specific fatty acid transport protein 6 is associated with lower fasting and postprandial TAG, blood pressure and left ventricular hypertrophy

Fatty acid transport protein 6 (FATP6) is primarily expressed in the heart and seems to be involved in cardiac fatty acid uptake. Therefore, we investigated whether a variation in the 5'-untranslated region of the FATP6 gene is associated with features of the metabolic syndrome and signs of myocardial alteration or heart failure. A total of 755 male participants from a Metabolic Intervention Cohort Kiel were genotyped for the FATP6-7T>A polymorphism (rs2526246) and phenotyped for features of the metabolic syndrome. Participants underwent a glucose tolerance test and the postprandial assessment of metabolic variables after a standardised mixed meal. Left ventricular heart function was evaluated in fifty-four participants. Fasting (P = 0·01) and postprandial (P = 0·02) TAG concentrations were significantly lower in AA homozygotes when compared with wild-type carriers. Homozygosity of allele A was associated with significantly lower postprandial insulin concentrations after a glucose load and significantly lower systolic (P = 0·01) and diastolic (P = 0·01) blood pressure values compared with wild-type carriers. Accordingly, left ventricular heart mass was significantly lower in twenty-seven AA homozygotes in comparison with twenty-seven TT homozygotes, matched for BMI (P = 0·04). In conclusion, the effects of the FATP6 polymorphism on TAG are mediated by affluent dietary fat. The FATP6-7T>A polymorphism may protect from traits of the metabolic syndrome and CVD.

Cloning and expression pattern of alkaline phosphatase during the development of Paralichthys olivaceus

Alkaline phosphatases are ubiquitous enzymes involved in many important biological processes. Mammalian tissue-nonspecific alkaline phosphatase has long been thought to feature in embryonic development and bone formation. In this study, an alkaline phosphatase (ALP) gene from Paralichthys olivaceus was identified by rapid amplification of cDNA ends and genome-walking PCR. The ALP gene extends 10,141 bp and contains 11 exons and 10 introns. The open reading frame of the ALP transcript consists of 1,431 bp, which encodes 476 amino acids products named as POALP. An analysis of its secondary and tertiary structure revealed that the POALP was conserved in different species, but one disulfide linkage made it possible to adapt to low-temperature environment. The ALP activity was found to be first detectable in the embryo before hatching. The POALP was distributed ubiquitously in the body of P. olivaceus and was particularly high in the digestive tract. These findings suggest the potential role of POALP in nutrient absorption and transportation. During the pre-metamorphosis (F stage), ALP gene expression is 2.5-folds of that in the pro-metamorphosis (E stage); but in the post-metamorphosis (I stage), it was 1.8-folds of that of pro-metamorphosis. Exogenetic thyroxine (T4) and thiourea (TU) influenced the ALP gene expression significantly during the metamorphosis. Bioinformatics analysis showed that Japanese flounder ALP promoter region contained promoter sequence and putative recognition site for several transcriptional factors, including SREBP-1, SYR, and CdxA. In vitro promoter assays employing EGFP reporter system demonstrated that the promoter of ALP was active.

Activation of the glucocorticoid receptor is associated with poor prognosis in estrogen receptor-negative breast cancer

Estrogen receptor-negative (ER(-)) breast cancers have limited treatment options and are associated with earlier relapses. Because glucocorticoid receptor (GR) signaling initiates antiapoptotic pathways in ER(-) breast cancer cells, we hypothesized that activation of these pathways might be associated with poor prognosis in ER(-) disease. Here we report findings from a genome-wide study of GR transcriptional targets in a premalignant ER(-) cell line model of early breast cancer (MCF10A-Myc) and in primary early-stage ER(-) human tumors. Chromatin immunoprecipitation with massively parallel sequencing (ChIP-seq) coupled to time-course expression profiling led us to identify epithelial-to-mesenchymal transition (EMT) pathways as an important aspect associated with GR activation. We validated these findings by carrying out a meta-analysis of primary breast tumor gene expression from 1,378 early-stage breast cancer patients with long-term clinical follow-up, confirming that high levels of GR expression significantly correlated with shorter relapse-free survival in ER(-) patients who were treated or untreated with adjuvant chemotherapy. Notably, in ER(+) breast cancer patients, high levels of GR expression in tumors were significantly associated with better outcome relative to low levels of GR expression. Gene expression analysis revealed that ER(-) tumors expressing high GR levels exhibited differential activation of EMT, cell adhesion, and inflammation pathways. Our findings suggest a direct transcriptional role for GR in determining the outcome of poor-prognosis ER(-) breast cancers.

Characterization of two common 5' polymorphisms in PEX1 and correlation to survival in PEX1 peroxisome biogenesis disorder patients

Background

Mutations in PEX1 are the most common primary cause of Zellweger syndrome. In addition to exonic mutations, deletions and splice site mutations two 5' polymorphisms at c.-137 and c.-53 with a potential influence on PEX1 protein levels have been described in the 5' untranslated region (UTR) of the PEX1 gene.

Methods

We used RACE and in silico promoter prediction analysis to study the 5' UTR of PEX1. We determined the distribution of PEX1 5' polymorphisms in a cohort of 30 Zellweger syndrome patients by standard DNA sequencing. 5' polymorphisms were analysed in relation to the two most common mutations in PEX1 and were incorporated into a novel genotype-phenotype analysis by correlation of three classes of PEX1 mutations with patient survival.

Results

We provide evidence that the polymorphism 137 bp upstream of the ATG codon is not part of the UTR, rendering it a promoter polymorphism. We show that the first, but not the second most common PEX1 mutation arose independently of a specific upstream polymorphic constellation. By genotype-phenotype analysis we identified patients with identical exonic mutation and identical 5' polymorphisms, but strongly differing survival.

Conclusions

Our study suggests that two different types of PEX1 5' polymorphisms have to be distinguished: a 5' UTR polymorphism at position c.-53 and a promoter polymorphism 137 bp upstream of the PEX1 start codon. Our results indicate that the exonic PEX1 mutation correlates with patient survival, but the two 5' polymorphisms analysed in this study do not have to be considered for diagnostic and/or prognostic purposes.

Functional analysis of the DAT gene promoter using transient Catharanthus roseus and stable Nicotiana tabacum transformation systems

The Catharanthus roseus DAT gene encodes the enzyme acetyl-CoA:deacetylvindoline-4-O-acetyltransferase involved in the last step of the indole alkaloid pathway leading to vindoline. This gene is characterized by specific cell type expression in idioblasts and laticifers. To understand the specific transcriptional regulation mechanism(s) of DAT, several DAT promoter GUS constructs were cloned into pCAMBIA1305.1. Agroinfiltration of different explant types of C. roseus resulted in organ-specific accumulation of GUS, albeit at various levels. Heterologous accumulation of GUS in transgenic tobacco revealed both general and non-specific expression with the exception of a stomata-specific expression when 2.3 kb of the DAT promoter was coupled with a portion of the DAT ORF. These results suggest that in addition to the 2.3 kb upstream of the DAT transcriptional start site, additional cis-acting elements may be responsible for the specific spatial expression of DAT in vivo. Furthermore, hairy roots transformed with DAT promoter GUS constructs demonstrated GUS expression in root tissues (visualized through GUS enzyme activity), even though DAT is repressed in non-transformed roots.

Polymorphisms in promoter sequences of MDM2, p53, and p16 genes in normal Japanese individuals

Research has been conducted to identify sequence polymorphisms of gene promoter regions in patients and control subjects, including normal individuals, and to determine the influence of these polymorphisms on transcriptional regulation in cells that express wild-type or mutant p53. In this study we isolated genomic DNA from whole blood of healthy Japanese individuals and sequenced the promoter regions of the MDM2, p53, and p16(INK4a) genes. We identified polymorphisms comprising 3 nucleotide substitutions at exon 1 and intron 1 regions of the MDM2 gene and 1 nucleotide insertion at a poly(C) nucleotide position in the p53 gene. The Japanese individuals also exhibited p16(INK4a) polymorphisms at several positions, including position -191. Reporter gene analysis by using luciferase revealed that the polymorphisms of MDM2, p53, and p16(INK4a) differentially altered luciferase activities in several cell lines, including the Colo320DM, U251, and T98G cell lines expressing mutant p53. Our results indicate that the promoter sequences of these genes differ among normal Japanese individuals and that polymorphisms can alter gene transcription activity.

A linear model for transcription factor binding affinity prediction in protein binding microarrays

Protein binding microarrays (PBM) are a high throughput technology used to characterize protein-DNA binding. The arrays measure a protein's affinity toward thousands of double-stranded DNA sequences at once, producing a comprehensive binding specificity catalog. We present a linear model for predicting the binding affinity of a protein toward DNA sequences based on PBM data. Our model represents the measured intensity of an individual probe as a sum of the binding affinity contributions of the probe's subsequences. These subsequences characterize a DNA binding motif and can be used to predict the intensity of protein binding against arbitrary DNA sequences. Our method was the best performer in the Dialogue for Reverse Engineering Assessments and Methods 5 (DREAM5) transcription factor/DNA motif recognition challenge. For the DREAM5 bonus challenge, we also developed an approach for the identification of transcription factors based on their PBM binding profiles. Our approach for TF identification achieved the best performance in the bonus challenge.

BINOCh: binding inference from nucleosome occupancy changes

Transcription factor binding events are frequently associated with a pattern of nucleosome occupancy changes in which nucleosomes flanking the binding site increase in occupancy, while those in the vicinity of the binding site itself are displaced. Genome-wide information on enhancer proximal nucleosome occupancy can be readily acquired using ChIP-seq targeting enhancer-related histone modifications such as H3K4me2. Here, we present a software package, BINOCh that allows biologists to use such data to infer the identity of key transcription factors that regulate the response of a cell to a stimulus or determine a program of differentiation.

AVAILABILITY

The BINOCh open source Python package is freely available at http://liulab.dfci.harvard.edu/BINOCh under the FreeBSD license.

Improved similarity scores for comparing motifs

MOTIVATION

A question that often comes up after applying a motif finder to a set of co-regulated DNA sequences is whether the reported putative motif is similar to any known motif. While several tools have been designed for this task, Habib et al. pointed out that the scores that are commonly used for measuring similarity between motifs do not distinguish between a good alignment of two informative columns (say, all-A) and one of two uninformative columns. This observation explains why tools such as Tomtom occasionally return an alignment of uninformative columns which is clearly spurious. To address this problem, Habib et al. suggested a new score [Bayesian Likelihood 2-Component (BLiC)] which uses a Bayesian information criterion to penalize matches that are also similar to the background distribution.

RESULTS

We show that the BLiC score exhibits other, highly undesirable properties, and we offer instead a general approach to adjust any motif similarity score so as to reduce the number of reported spurious alignments of uninformative columns. We implement our method in Tomtom and show that, without significantly compromising Tomtom's retrieval accuracy or its runtime, we can drastically reduce the number of uninformative alignments.

AVAILABILITY AND IMPLEMENTATION

The modified Tomtom is available as part of the MEME Suite at http://meme.nbcr.net.

Multiple sequence-specific DNA-binding proteins mediate estrogen receptor signaling through a tethering pathway

The indirect recruitment (tethering) of estrogen receptors (ERs) to DNA through other DNA-bound transcription factors (e.g. activator protein 1) is an important component of estrogen-signaling pathways, but our understanding of the mechanisms of ligand-dependent activation in this pathway is limited. Using proteomic, genomic, and gene-specific analyses, we demonstrate that a large repertoire of DNA-binding transcription factors contribute to estrogen signaling through the tethering pathway. In addition, we define a set of endogenous genes for which ERα tethering through activator protein 1 (e.g. c-Fos) and cAMP response element-binding protein family members mediates estrogen responsiveness. Finally, we show that functional interplay between c-Fos and cAMP response element-binding protein 1 contributes to estrogen-dependent regulation through the tethering pathway. Based on our results, we conclude that ERα recruitment in the tethering pathway is dependent on the ligand-induced formation of transcription factor complexes that involves interplay between the transcription factors from different protein families.

Predictive markers in calpastatin for tenderness in commercial pig populations

The identification of predictive DNA markers for pork quality would allow US pork producers and breeders to select genetically superior animals more quickly and efficiently for the production of consistent, high-quality meat. Genome scans have identified QTL for tenderness on SSC 2, which have been fine-mapped to the calpastatin locus. The objectives of this study were to identify the sequence variation in calpastatin that likely affects tenderness in commercial-level pig populations and to develop definitive DNA markers that are predictive of pork tenderness for use in marker-assisted selection programs. We resequenced the calpastatin regulatory and transcribed regions in pigs with divergently extreme shear force values to identify possible mutations that could affect tenderness. A total of 194 SNP were identified in this sequence, and 31 SNP were found in predicted transcription factor binding sites. We tested 131 polymorphisms in our research population and a subset (40) of these in samples of industry pigs for their association with objective measures of tenderness. We identified 4 SNP that were consistently associated with pork tenderness in all the populations studied, representing 2,826 pigs from 4 distinct populations. Gel shift assays were designed for these SNP and 12 other polymorphic sites. Six sites demonstrated a gel shift when probes were incubated with nuclear extract from muscle, heart, or testis. Four of these sites, a specificity protein 1 (Sp1) site around nucleotides 12978 and 12979, a potential thyrotroph embryonic factor (Tef) site at nucleotide 25587, an unknown site at nucleotide 48699, and myocyte enhancer factor-2 (Mef-2)/TATA sites with SNP at positions 49223 and 49228 were allele specific in binding nuclear proteins. The allele frequencies for the tender alleles were similar (0.11 to 0.36) in the 4 different commercial populations. These 4 SNP were not in complete linkage disequilibrium with each other and may independently affect calpastatin expression, tenderness, or both. These markers should be predictive of pork tenderness in industry populations.

PCR DNA-array profiling of DNA-binding transcription factor activities in adult mouse tissues

Differential gene expression is tightly controlled by transcription factors (TFs), which bind close to target genes and interact together to activate and coregulate transcription. Bioinformatics analysis of published genome-wide gene expression data has allowed the development of comprehensive models of TFs likely to be active in particular tissues (signature TFs); however, the predicted activities of many of the TFs have not been experimentally confirmed. Here, we describe methods for the parallel analysis of the activities of more than 200 transcription factor proteins, using an advanced oligonucleotide array-based transcription factor assay (OATFA) platform, to assay TF activities in mice. The system uses a PCR-based system to translate cellular levels of target DNA-TF complex into a dye-tagged DNA signal, which is read by the developed microarray. The PCR step introduces semiquantitative amplification of the represented TF binding sequences. Experimental OATFA findings can identify many TF activities, which bioinformatics profiling does not predict. Newly identified TF activities can be confirmed by antibody-ELISA against active TFs. The PCR-based OATFA microarray analysis is a comprehensive method that can be used to reveal transcriptional systems and pathways which may function in different mammalian tissues and cells.

Interferon regulatory factor 3 (IRF-3) in Japanese flounder, Paralichthys olivaceus: sequencing, limited tissue distribution, inducible expression and induction of fish type I interferon promoter

Two cDNAs with different 3'-untranslated region (UTR) encoding an interferon regulatory factor 3 (IRF-3) were cloned from head kidney of Japanese flounder, Paralichthys olivaceus, by reverse transcription polymerase chain reaction (RT-PCR) and rapid amplification of cDNA ends (RACE) methods. Sequence analysis reveals that they were generated by alternative polyadenylation. The predicted protein consists of 467 amino acid residues which shares the highest identity of 50.7-57.6% to fish IRF-3 and possesses a DNA-binding domain (DBD), an IRF association domain (IAD) and a serine-rich domain (SRD) of vertebrate IRF-3. The presence of these domains along with phylogenetic analysis places it into the IRF-3 group of the IRF-3 subfamily. RT-PCR analysis revealed that flounder IRF-3 was expressed constitutively in limited tissue types including head kidney, spleen, kidney, heart, gill, intestine and liver. A quantitative real time PCR assay was employed to monitor expression of IRF-3, type I interferon (IFN) and Mx in flounder head kidney and gill. All three genes were up-regulated by polyinosinic:polycytidylic acid (polyI:C) and lymphocystis disease virus (LCDV) with an earlier but slight and less persistent increase in transcription levels seen for the IRF-3. Finally, flounder IRF-3 was proved to induce fish type I IFN promoter in FG9307 cells, a flounder gill cell line, by a luciferase assay. These results provide insights into the roles of fish IRF-3 in the antiviral immunity.

Signatures of murine B-cell development implicate Yy1 as a regulator of the germinal center-specific program

We utilized gene expression profiling of a comprehensive panel of purified developmentally defined normal murine B cells to identify unique transcriptional signatures for each subset. To elucidate transcription factor activities that function in a stage-specific fashion, we used gene sets that share transcription factor targets and found that germinal center B cells had a robust enrichment of up-regulated and down-regulated signatures compared with the other B-cell subsets. Notably, we found Yy1 and its targets to be central regulators of the germinal center B (GCB)-specific transcriptional program with binding of Yy1 to select signature genes in GCB cells, and translation of the Yy1 signatures to human GCB cells. We then tested whether our newly generated, stage-specific transcriptional signatures could be used to link murine lymphoma models to stages of normal B-cell development. Although each of the molecularly defined murine lymphoma models conserved certain stage-specific features of normal B-cell development, there was a significant alteration of the normal differentiation signature following malignant transformation. These findings offer important tools and insights for elucidating differences between normal and malignant B cells.

The missing association: sequencing-based discovery of novel SNPs in VKORC1 and CYP2C9 that affect warfarin dose in African Americans

It is well recognized that the genetic variants VKORC1-1639, CYP2C9*2, and CYP2C9*3 contribute to warfarin dose response. This has led to warfarin dosing algorithms that include these polymorphisms and explains between 47% and 56% of variability in dose in Caucasians. However, these polymorphisms explain significantly less of the variance in dose among African Americans. In order to identify novel variations that affect warfarin dose in African Americans, we used a targeted resequencing strategy that examined evolutionarily conserved sequences and regions of putative transcriptional binding. Through ethnicity-specific warfarin dose model building in 330 African Americans, we identified two novel genetic associations with higher warfarin dose, namely, VKORC1-8191 (rs61162043, P = 0.0041) and 18786 in CYP2C9 (rs7089580, P = 0.035). These novel finds are independent of the previous associations with these genes. Our regression model, encompassing both genetic and clinical variables, explained 40% of the variability in warfarin dose in African-American subjects, significantly more than any model thus far.

The NFI-Regulome Database: A tool for annotation and analysis of control regions of genes regulated by Nuclear Factor I transcription factors

BACKGROUND

Genome annotation plays an essential role in the interpretation and use of genome sequence information. While great strides have been made in the annotation of coding regions of genes, less success has been achieved in the annotation of the regulatory regions of genes, including promoters, enhancers/silencers, and other regulatory elements. One reason for this disparity in annotated information is that coding regions can be assessed using high-throughput techniques such as EST sequencing, while annotation of regulatory regions often requires a gene-by-gene approach.

RESULTS

The NFI-Regulome database http://nfiregulome.ccr.buffalo.edu was designed to promote easy annotation of the regulatory regions of genes that contain binding sites for the NFI (Nuclear Factor I) family of transcription factors, using data from the published literature. Binding sites are annotated together with the sequence of the gene, obtained from the UCSC Genome site, and the locations of all binding sites for multiple genes can be displayed in a number of formats designed to facilitate inter-gene comparisons. Classes of genes based on expression pattern, disease involvement, or types of binding sites present can be readily compared in order to assess common "architectural" structures in the regulatory regions.

CONCLUSIONS

The NFI-Regulome database allows rapid display of the relative locations and number of transcription factor binding sites of individual or defined sets of genes that contain binding sites for NFI transcription factors. This database may in the future be expanded into a distributed database structure including other families of transcription factors. Such databases may be useful for identifying common regulatory structures in genes essential for organ development, tissue-specific gene expression or those genes related to specific diseases.

Heterogeneity in DNA multiple alignments: modeling, inference, and applications in motif finding

Transcription factors bind sequence-specific sites in DNA to regulate gene transcription. Identifying transcription factor binding sites (TFBSs) is an important step for understanding gene regulation. Although sophisticated in modeling TFBSs and their combinatorial patterns, computational methods for TFBS detection and motif finding often make oversimplified homogeneous model assumptions for background sequences. Since nucleotide base composition varies across genomic regions, it is expected to be helpful for motif finding to incorporate the heterogeneity into background modeling. When sequences from multiple species are utilized, variation in evolutionary conservation violates the common assumption of an identical conservation level in multiple alignments. To handle both types of heterogeneity, we propose a generative model in which a segmented Markov chain is used to partition a multiple alignment into regions of homogeneous nucleotide base composition and a hidden Markov model (HMM) is employed to account for different conservation levels. Bayesian inference on the model is developed via Gibbs sampling with dynamic programming recursions. Simulation studies and empirical evidence from biological data sets reveal the dramatic effect of background modeling on motif finding, and demonstrate that the proposed approach is able to achieve substantial improvements over commonly used background models.

High-throughput analyses and curation of protein interactions in yeast

The yeast Saccharomyces cerevisiae is the model organism in which protein interactions have been most extensively analyzed. The vast majority of these interactions have been characterized by a variety of sophisticated high-throughput techniques probing different aspects of protein association. This chapter summarizes the major techniques, highlights their complementary nature, discusses the data they produce, and highlights some of the biases from which they suffer. A main focus is the key role played by computational methods for processing, analyzing, and validating the large body of noisy data produced by the experimental procedures. It also describes how computational methods are used to extend the coverage and reliability of protein interaction data by integrating information from heterogeneous sources and reviews the current status of literature-curated data on yeast protein interactions stored in specialized databases.

A novel HMM-based method for detecting enriched transcription factor binding sites reveals RUNX3 as a potential target in pancreatic cancer biology

BACKGROUND

Pancreatic adenocarcinoma (PAC) is one of the most intractable malignancies. In order to search for potential new therapeutic targets, we relied on computational methods aimed at identifying transcription factor binding sites (TFBSs) over-represented in the promoter regions of genes differentially expressed in PAC. Though many computational methods have been implemented to accomplish this, none has gained overall acceptance or produced proven novel targets in PAC. To this end we have developed DEMON, a novel method for motif detection.

METHODOLOGY

DEMON relies on a hidden Markov model to score the appearance of sequence motifs, taking into account all potential sites in a promoter of potentially varying binding affinities. We demonstrate DEMON's accuracy on simulated and real data sets. Applying DEMON to PAC-related data sets identifies the RUNX family as highly enriched in PAC-related genes. Using a novel experimental paradigm to distinguish between normal and PAC cells, we find that RUNX3 mRNA (but not RUNX1 or RUNX2 mRNAs) exhibits time-dependent increases in normal but not in PAC cells. These increases are accompanied by changes in mRNA levels of putative RUNX gene targets.

CONCLUSIONS

The integrated application of DEMON and a novel differentiation system led to the identification of a single family member, RUNX3, which together with four of its putative targets showed a robust response to a differentiation stimulus in healthy cells, whereas this regulatory mechanism was absent in PAC cells, emphasizing RUNX3 as a promising target for further studies.

Inference of hierarchical regulatory network of estrogen-dependent breast cancer through ChIP-based data

Background

Global profiling of in vivo protein-DNA interactions using ChIP-based technologies has evolved rapidly in recent years. Although many genome-wide studies have identified thousands of ERα binding sites and have revealed the associated transcription factor (TF) partners, such as AP1, FOXA1 and CEBP, little is known about ERα associated hierarchical transcriptional regulatory networks.

Results

In this study, we applied computational approaches to analyze three public available ChIP-based datasets: ChIP-seq, ChIP-PET and ChIP-chip, and to investigate the hierarchical regulatory network for ERα and ERα partner TFs regulation in estrogen-dependent breast cancer MCF7 cells. 16 common TFs and two common new TF partners (RORA and PITX2) were found among ChIP-seq, ChIP-chip and ChIP-PET datasets. The regulatory networks were constructed by scanning the ChIP-peak region with TF specific position weight matrix (PWM). A permutation test was performed to test the reliability of each connection of the network. We then used DREM software to perform gene ontology function analysis on the common genes. We found that FOS, PITX2, RORA and FOXA1 were involved in the up-regulated genes.

We also conducted the ERα and Pol-II ChIP-seq experiments in tamoxifen resistance MCF7 cells (denoted as MCF7-T in this study) and compared the difference between MCF7 and MCF7-T cells. The result showed very little overlap between these two cells in terms of targeted genes (21.2% of common genes) and targeted TFs (25% of common TFs). The significant dissimilarity may indicate totally different transcriptional regulatory mechanisms between these two cancer cells.

Conclusions

Our study uncovers new estrogen-mediated regulatory networks by mining three ChIP-based data in MCF7 cells and ChIP-seq data in MCF7-T cells. We compared the different ChIP-based technologies as well as different breast cancer cells. Our computational analytical approach may guide biologists to further study the underlying mechanisms in breast cancer cells or other human diseases.

ZNF274 recruits the histone methyltransferase SETDB1 to the 3' ends of ZNF genes

Only a small percentage of human transcription factors (e.g. those associated with a specific differentiation program) are expressed in a given cell type. Thus, cell fate is mainly determined by cell type-specific silencing of transcription factors that drive different cellular lineages. Several histone modifications have been associated with gene silencing, including H3K27me3 and H3K9me3. We have previously shown that genes for the two largest classes of mammalian transcription factors are marked by distinct histone modifications; homeobox genes are marked by H3K27me3 and zinc finger genes are marked by H3K9me3. Several histone methyltransferases (e.g. G9a and SETDB1) may be involved in mediating the H3K9me3 silencing mark. We have used ChIP-chip and ChIP-seq to demonstrate that SETDB1, but not G9a, is associated with regions of the genome enriched for H3K9me3. One current model is that SETDB1 is recruited to specific genomic locations via interaction with the corepressor TRIM28 (KAP1), which is in turn recruited to the genome via interaction with zinc finger transcription factors that contain a Kruppel-associated box (KRAB) domain. However, specific KRAB-ZNFs that recruit TRIM28 (KAP1) and SETDB1 to the genome have not been identified. We now show that ZNF274 (a KRAB-ZNF that contains 5 C2H2 zinc finger domains), can interact with KAP1 both in vivo and in vitro and, using ChIP-seq, we show that ZNF274 binding sites co-localize with SETDB1, KAP1, and H3K9me3 at the 3′ ends of zinc finger genes. Knockdown of ZNF274 with siRNAs reduced the levels of KAP1 and SETDB1 recruitment to the binding sites. These studies provide the first identification of a KRAB domain-containing ZNF that is involved in recruitment of the KAP1 and SETDB1 to specific regions of the human genome.

Assessing computational methods of cis-regulatory module prediction

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

FlyFactorSurvey: a database of Drosophila transcription factor binding specificities determined using the bacterial one-hybrid system

FlyFactorSurvey (http://pgfe.umassmed.edu/TFDBS/) is a database of DNA binding specificities for Drosophila transcription factors (TFs) primarily determined using the bacterial one-hybrid system. The database provides community access to over 400 recognition motifs and position weight matrices for over 200 TFs, including many unpublished motifs. Search tools and flat file downloads are provided to retrieve binding site information (as sequences, matrices and sequence logos) for individual TFs, groups of TFs or for all TFs with characterized binding specificities. Linked analysis tools allow users to identify motifs within our database that share similarity to a query matrix or to view the distribution of occurrences of an individual motif throughout the Drosophila genome. Together, this database and its associated tools provide computational and experimental biologists with resources to predict interactions between Drosophila TFs and target cis-regulatory sequences.

Patterns of human gene expression variance show strong associations with signaling network hierarchy

Background

Understanding organizational principles of cellular networks is one of the central goals of systems biology. Although much has been learnt about gene expression programs under specific conditions, global patterns of expressional variation (EV) of genes and their relationship to cellular functions and physiological responses is poorly understood.

Results

To understand global principles of relationship between transcriptional regulation of human genes and their functions, we have leveraged large-scale datasets of human gene expression measurements across a wide spectrum of cell conditions. We report that human genes are highly diverse in terms of their EV; while some genes have highly variable expression pattern, some seem to be relatively ubiquitously expressed across a wide range of conditions. The wide spectrum of gene EV strongly correlates with the positioning of proteins within the signaling network hierarchy, such that, secreted extracellular receptor ligands and membrane receptors have the highest EV, and intracellular signaling proteins have the lowest EV in the genome. Our analysis shows that this pattern of EV reflects functional centrality: proteins with highly specific signaling functions are modulated more frequently than those with highly central functions in the network, which is also consistent with previous studies on tissue-specific gene expression. Interestingly, these patterns of EV along the signaling network hierarchy have significant correlations with promoter architectures of respective genes.

Conclusion

Our analyses suggest a generic systems level mechanism of regulation of the cellular signaling network at the transcriptional level.

Hidden Markov model and its applications in motif findings

Hidden Markov models have wide applications in pattern recognition. In genome sequence analysis, hidden Markov models (HMMs) have been applied to the identification of regions of the genome that contain regulatory information, i.e., binding sites. In higher eukaryotes, the regulatory information is organized into modular units called cis-regulatory modules. Each module contains multiple binding sites for a specific combination of several transcription factors. In this chapter, we gave a brief review of hidden Markov models, standard algorithms from HMM, and their applications to motif findings. We then introduce the application of HMM to a complex system in which an HMM is combined with Bayesian inference to identify transcription factor binding sites and cis-regulatory modules.

A parallel scheme for comparing transcription factor binding sites matrices

Gene regulation implies many mechanisms. Their identification is a crucial task to construct regulatory networks, and is necessary to understand the pathology in many cases. This requires the identification of transcription factors that play a role in regulation. Numerous motif discovery tools are now available. Combining efficiently their results appears useful for comparing and clustering these motifs in order to reduce redundancies and to identify the corresponding transcription factor. We develop a method that produces, compares and clusters a set of motifs and identifies some close motifs in databases like JASPAR and the public version of Transfac. Unlike previous comparison methods, where each matrix column is compared independently, we have developed a global method to compare motifs that also helps to reduce the number of false positives. We also propose an original graph motif model that generalizes the classical position specific pattern matrices. Finally, we present an application of our method to study ChIP-chip data sets in the context of an eukaryotic organism.

Evolutionary analysis of regulatory sequences (EARS) in plants

Identification of regulatory sequences within non-coding regions of DNA is an essential step towards elucidation of gene networks. This approach constitutes a major challenge, however, as only a very small fraction of non-coding DNA is thought to contribute to gene regulation. The mapping of regulatory regions traditionally involves the laborious construction of promoter deletion series which are then fused to reporter genes and assayed in transgenic organisms. Bioinformatic methods can be used to scan sequences for matches for known regulatory motifs, however these methods are currently hampered by the relatively small amount of such motifs and by a high false-discovery rate. Here, we demonstrate a robust and highly sensitive, in silico method to identify evolutionarily conserved regions within non-coding DNA. Sequence conservation within these regions is taken as evidence for evolutionary pressure against mutations, which is suggestive of functional importance. We test this method on a small set of well characterised promoters, and show that it successfully identifies known regulatory regions. We further show that these evolutionarily conserved sequences contain clusters of transcription binding sites, often described as regulatory modules. A version of the tool optimised for the analysis of plant promoters is available online at http://wsbc.warwick.ac.uk/ears/main.php.

Polymorphisms in promoter sequences of the p15 ( INK4B ) and PTEN genes of normal Japanese individuals

Gene promoter regions of p15(INK4B), a cyclin-dependent kinase inhibitor, and phosphatase and tensin homolog (PTEN), a dual-function protein and lipid phosphatase, interact with regulatory factors for gene transcription and methylation. Normal individuals exhibit sequence polymorphisms in these regulatory genes. We isolated genomic DNA from whole blood of healthy Japanese individuals and sequenced promoter regions of the p15 ( INK4B ) and PTEN genes. We also examined the influence of polymorphisms on promoter activity in several cell lines. We identified polymorphisms at positions -699, -394, and -242 and an insertion at position -320 in the p15 ( INK4B ) gene and a polymorphism at position -1142 in the PTEN gene. Reporter gene analysis revealed that these polymorphisms influenced transcriptional regulation in their cell lines. Our results indicate for the first time that promoter sequences of the p15 ( INK4B ) and PTEN genes differ among normal Japanese individuals and that promoter polymorphisms can influence gene transcription.

Molecular cloning of rhamnose-binding lectin gene and its promoter region from snakehead Channa argus

Lectins are sugar-binding proteins that mediate pathogen recognition and cell-cell interactions. A rhamnose-binding lectin (RBL) gene and its promoter region have been cloned and characterized from snakehead Channa argus. From the transcription initiation site, snakehead rhamnose-binding lectin (SHL) gene extends 2,382 bp to the end of the 3' untranslated region (UTR), and contains nine exons and eight introns. The open reading frame (ORF) of the SHL transcript has 675 bp which encodes 224 amino acids. The molecular structure of SHL is composed of two tandem repeat carbohydrate recognition domains (CRD) with 35% internal identity. Analysis of the gene organization of SHL indicates that the ancestral gene of RBL may diverge and evolve by exon shuffling and gene duplication, producing new forms to play their own roles in various organisms. The characteristics of SHL gene 5' flanking region are the presence of consensus nuclear factor of interleukin 6 (NF-IL6) and IFN-gamma activation (GAS) sites. The results provide indirect evidence that up-regulation of SHL expression may be induced in response to inflammatory stimuli, such as lipopolysaccharide (LPS), interleukin 6 (IL-6), and interferon gamma (IFN-gamma). The transcript of SHL mRNA was expressed in the head kidney, posterior kidney, spleen, liver, intestine, heart, muscle, and ovary. No tissue-specific expressive pattern is different from reported STLs, WCLs, and PFLs, suggesting that different types of RBLs exist in species-specific fish that have evolved and adapted to their surroundings.

Use of data-biased random walks on graphs for the retrieval of context-specific networks from genomic data

Extracting network-based functional relationships within genomic datasets is an important challenge in the computational analysis of large-scale data. Although many methods, both public and commercial, have been developed, the problem of identifying networks of interactions that are most relevant to the given input data still remains an open issue. Here, we have leveraged the method of random walks on graphs as a powerful platform for scoring network components based on simultaneous assessment of the experimental data as well as local network connectivity. Using this method, NetWalk, we can calculate distribution of Edge Flux values associated with each interaction in the network, which reflects the relevance of interactions based on the experimental data. We show that network-based analyses of genomic data are simpler and more accurate using NetWalk than with some of the currently employed methods. We also present NetWalk analysis of microarray gene expression data from MCF7 cells exposed to different doses of doxorubicin, which reveals a switch-like pattern in the p53 regulated network in cell cycle arrest and apoptosis. Our analyses demonstrate the use of NetWalk as a valuable tool in generating high-confidence hypotheses from high-content genomic data.

Transcriptional regulation by CHIP/LDB complexes

It is increasingly clear that transcription factors play versatile roles in turning genes "on" or "off" depending on cellular context via the various transcription complexes they form. This poses a major challenge in unraveling combinatorial transcription complex codes. Here we use the powerful genetics of Drosophila combined with microarray and bioinformatics analyses to tackle this challenge. The nuclear adaptor CHIP/LDB is a major developmental regulator capable of forming tissue-specific transcription complexes with various types of transcription factors and cofactors, making it a valuable model to study the intricacies of gene regulation. To date only few CHIP/LDB complexes target genes have been identified, and possible tissue-dependent crosstalk between these complexes has not been rigorously explored. SSDP proteins protect CHIP/LDB complexes from proteasome dependent degradation and are rate-limiting cofactors for these complexes. By using mutations in SSDP, we identified 189 down-stream targets of CHIP/LDB and show that these genes are enriched for the binding sites of APTEROUS (AP) and PANNIER (PNR), two well studied transcription factors associated with CHIP/LDB complexes. We performed extensive genetic screens and identified target genes that genetically interact with components of CHIP/LDB complexes in directing the development of the wings (28 genes) and thoracic bristles (23 genes). Moreover, by in vivo RNAi silencing we uncovered novel roles for two of the target genes, xbp1 and Gs-alpha, in early development of these structures. Taken together, our results suggest that loss of SSDP disrupts the normal balance between the CHIP-AP and the CHIP-PNR transcription complexes, resulting in down-regulation of CHIP-AP target genes and the concomitant up-regulation of CHIP-PNR target genes. Understanding the combinatorial nature of transcription complexes as presented here is crucial to the study of transcription regulation of gene batteries required for development.

Flanking region sequence information to refine microRNA target predictions

The non-coding elements of a genome, with many of them considered as junk earlier, have now started gaining long due respectability, with microRNAs as the best current example. MicroRNAs bind preferentially to the 3' untranslated regions 9UTRs) of the target genes and negatively regulate their expression most of the time. Several microRNA: target prediction softwares have been developed based upon various assumptions and the majority of them consider the free energy of binding of a target to its microRNA and seed conservation. However, the average concordance between the predictions made by these softwares is limited and compounded by a large number of false-positive results. In this study, we describe a methodology developed by us to refine microRNA: target prediction by target prediction softwares through observations made from a comprehensive study. We incorporated the information obtained from dinucleotide content variation patterns recorded for flanking regions around the target sites using support vector machines (SVMs) trained over two different major sources of experimental data, besides other sources. We assessed the performance of our methodology with rigorous tests over four different dataset models and also compared it with a recently published refinement tool, MirTif. Our methodology attained a higher average accuracy of 0.88, average sensitivity and specificity of 0.81 and 0.94, respectively, and areas under the curves (AUCs) for all the four models scored above 0.9, suggesting better performance by our methodology and a possible role of flanking regions in microRNA targeting control. We used our methodology over genes of three different pathways--toll-like receptor (TLR), apoptosis and insulin--to finally predict the most probable targets. We also investigated their possible regulatory associations, and identified a hsa-miR-23a regulatory module.

Appearance of the pituitary factor Pit-1 increases chromatin remodeling at hypersensitive site III in the human GH locus

Expression of pituitary and placental members of the human GH and chorionic somatomammotropin (CS) gene family is directed by an upstream remote locus control region (LCR). Pituitary-specific expression of GH requires direct binding of Pit-1 (listed as POU1F1 in the HUGO database) to sequences marked by a hypersensitive site (HS) region (HS I/II) 14.6 kb upstream of the GH-N gene (listed as GH1 in the HUGO database). We used human embryonic kidney 293 (HEK293) cells overexpressing wild-type and mutant Pit-1 proteins as a model system to gain insight into the mechanism by which Pit-1 gains access to the GH LCR. Addition of Pit-1 to these cells increased DNA accessibility at HS III, located 28 kb upstream of the human GH-N gene, in a POU homeodomain-dependent manner, as reflected by effects on histone hyperacetylation and RNA polymerase II activity. Direct binding of Pit-1 to HS III sequences is not supported. However, the potential for binding of ETS family members to this region has been demonstrated, and Pit-1 association with this ETS element in HS III sequences requires the POU homeodomain. Also, both ETS1 and ELK1 co-precipitate from human pituitary extracts using two independent sources of Pit-1 antibodies. Finally, overexpression of ELK1 or Pit-1 expression in HEK293 cells increased GH-N RNA levels. However, while ELK1 overexpression also stimulated placental CS RNA levels, the effect of Pit-1 appeared to correlate with ETS factor levels and target GH-N preferentially. These data are consistent with recruitment and an early role for Pit-1 in remodeling of the GH LCR at the constitutively open HS III through protein-protein interaction.

Systematic analysis of regulation and functions of co-expressed microRNAs in humans

MicroRNAs (miRNAs) are a class of small non-coding RNA genes that post-transcriptionally regulate gene expression. With the development of high-throughput miRNA detection technology, researchers have begun to investigate the relationships between miRNA expression and its functions. In this study, we systematically analyzed the underlying molecular mechanisms and biological functions of co-expressed miRNAs. By integrating miRNA expression profiles, miRNA genome locations, transcriptional factors (TFs) of miRNAs and their target genes, we concluded that co-expressed miRNAs are more likely to be located in the same miRNA cluster (p = 6.05 x 10(-30)), are regulated by more common TFs (p = 9.17 x 10(-17)) and have consistent functions (p = 1.01 x 10(-6)). Moreover, among the top 10% (84) co-expressed miRNA pairs that are located on the same chromosomes, 37 miRNA pairs are located in the same cluster. Of the remaining 47 pairs, 36 miRNA pairs share more common TFs (>7). They account for 73/84 (86.9%) of total miRNA pairs. Finally, we further analyzed the top 10 co-expressed miRNA pairs. Almost all of these miRNA pairs are located in the same cluster, are regulated by many common TFs and have highly consistent functions, in agreement with previous reports. Thus, our study may provide an important reference for miRNA regulations and functions.

Inhibition of AP-1 by SARI negatively regulates transformation progression mediated by CCN1

Enhanced expression of the CCN family of secretory integrin-binding proteins correlates with many essential components of the cancerous state, including tumor cell adhesion, proliferation, invasion and migration. Consequently, CCN1 expression is elevated in various cancers, including breast cancer, and its expression directly correlates with poor patient prognosis. Using subtraction-hybridization, combined with induction of cancer cell terminal differentiation, we cloned SARI (suppressor of activator protein (AP)-1, regulated by interferon (IFN)), an IFN-beta-inducible, potent tumor suppressor gene that exerts cancer-selective growth inhibitory effects. Forced expression of SARI using an adenovirus (Ad.SARI) inhibits AP-1 function and downregulates CCN1 expression in multiple cancer lineages, resulting in a profound inhibition in anchorage-independent cell growth and tumor cell invasion. Overexpression of SARI reduces CCN1-promoter activity through inhibition of AP-1 binding. Accordingly, SARI selectively blocks expression of the transformed state in rat embryo fibroblast cells that stably overexpress c-Jun. These results illustrate that SARI inhibits AP-1 transactivating factor binding to the cis-element of the CCN1 promoter, possibly through its interaction with c-Jun. Overall, SARI can directly inhibit CCN1-induced transformation by inhibiting the transcription of CCN1, as well as indirectly by inhibiting the expression of c-Jun (and hence blocking AP-1 activity). In these contexts, transformed cells 'addicted' to AP-1 activity are rendered susceptible to SARI-mediated inhibition of expression of the transformed phenotype.

Molecular mechanisms underlying sex change in hermaphroditic groupers

Groupers are widely distributed throughout the tropical and subtropical waters of the world and are regarded as a favourite marine food fish. However, their large-scale aquaculture has been hindered by the rarity of natural males. Being protogynous hermaphrodites, groupers have been considered as study model for development and reproduction, especially for sex determination or sex differentiation, owing to the advantage that grouper gonad development undergoes transition from ovary to intersexual gonad and then to testis, and primordial germ cells and different stages of gametic cells during oogenesis and spermatogenesis are synchronously observed in the transitional gonads. Recently, a series of genes related to the reproduction regulation or sex differentiation have been identified in the groupers, mainly by researchers in China. One important finding was that the grouper gene, doublesex/male abnormal 3-related transcription factor 1 (DMRT1), is not only differentially expressed in gonads at different stages, but that it is also restricted to specific stages and specific cells of spermatogenesis. Grouper DMRT1 protein exists only in spermatogonia, primary spermatocytes and secondary spermatocytes, but not in the supporting Sertoli cells. Moreover, no introns were found in the grouper DMRT1, and no duplicated DMRT1 genes were detected. The finding implies that the intronless DMRT1 that is able to undergo rapid transcriptional turnover might be a significant gene for stimulating spermatogenesis in the protogynous hermaphroditic gonad. Additionally, we have found that grouper expression of sex-determining region Y-related high-mobility group-box gene 3 (SOX3) is a significant time point for enterable gametogenesis of primordial germ cells, because SOX3 is obviously expressed and localized in primordial germ cells. As SOX3 continues to express, the SOX3-positive primordial germ cells develop toward oogonia and then oocytes, whereas, when SOX3 expression is ceased, the SOX3-positive primordial germ cells develop toward spermatogonia. Therefore, we suggest that SOX3, as a transcription factor, might have more important roles in oogenesis than in spermatogenesis. Based on the findings, a hypothetic molecular mechanism underlying sex change is proposed in the hermaphroditic groupers, and some candidate genes related to the grouper sex change are also suggested for further research.

Bioinformatic identification and characterization of human endothelial cell-restricted genes

Background

In this study, we used a systematic bioinformatics analysis approach to elucidate genes that exhibit an endothelial cell (EC) restricted expression pattern, and began to define their regulation, tissue distribution, and potential biological role.

Results

Using a high throughput microarray platform, a primary set of 1,191 transcripts that are enriched in different primary ECs compared to non-ECs was identified (LCB >3, FDR <2%). Further refinement of this initial subset of transcripts, using published data, yielded 152 transcripts (representing 109 genes) with different degrees of EC-specificity. Several interesting patterns emerged among these genes: some were expressed in all ECs and several were restricted to microvascular ECs. Pathway analysis and gene ontology demonstrated that several of the identified genes are known to be involved in vasculature development, angiogenesis, and endothelial function (P < 0.01). These genes are enriched in cardiovascular diseases, hemorrhage and ischemia gene sets (P < 0.001). Most of the identified genes are ubiquitously expressed in many different tissues. Analysis of the proximal promoter revealed the enrichment of conserved binding sites for 26 different transcription factors and analysis of the untranslated regions suggests that a subset of the EC-restricted genes are targets of 15 microRNAs. While many of the identified genes are known for their regulatory role in ECs, we have also identified several novel EC-restricted genes, the function of which have yet to be fully defined.

Conclusion

The study provides an initial catalogue of EC-restricted genes most of which are ubiquitously expressed in different endothelial cells.

Computational analysis of gene regulation in animal sleep deprivation

Sleep is an animal behavior shared by a wide range of species, suggesting that it must serve fundamental functions. However, the functions and molecular mechanisms underlying sleep are largely unknown. Through a meta-analysis of all available short-term sleep deprivation (SD) microarray data in mouse brain, we identified 91 key mouse SD-affected genes and two RBM3 isoforms showing opposite changes of expression during SD. Although most of the key SD-affected genes showed consistent changes of expression during SD across brain subregions despite their heterogeneous basal expression levels, we also identified the genes whose SD responses strongly depend upon the brain subregion. A gene regulatory network was also constructed for these genes showing that cAMP-responsive element (CRE) is one of the key cis-regulatory elements controlling SD-affected genes. We observed that SD during an animal's normal sleeping time could significantly disturb the circadian oscillation of clock genes. Surprisingly, synaptogenesis markers were significantly underexpressed in SD mice, differing from the previous findings in rat and fly. Comparing SD microarray data in mouse, rat, sparrow, and fly, we identified Egr and Nr4a gene families as conserved SD-affected genes, thus shedding new light on the origin of sleep in animals.

Coordinated modular functionality and prognostic potential of a heart failure biomarker-driven interaction network

Background

The identification of potentially relevant biomarkers and a deeper understanding of molecular mechanisms related to heart failure (HF) development can be enhanced by the implementation of biological network-based analyses. To support these efforts, here we report a global network of protein-protein interactions (PPIs) relevant to HF, which was characterized through integrative bioinformatic analyses of multiple sources of "omic" information.

Results

We found that the structural and functional architecture of this PPI network is highly modular. These network modules can be assigned to specialized processes, specific cellular regions and their functional roles tend to partially overlap. Our results suggest that HF biomarkers may be defined as key coordinators of intra- and inter-module communication. Putative biomarkers can, in general, be distinguished as "information traffic" mediators within this network. The top high traffic proteins are encoded by genes that are not highly differentially expressed across HF and non-HF patients. Nevertheless, we present evidence that the integration of expression patterns from high traffic genes may support accurate prediction of HF. We quantitatively demonstrate that intra- and inter-module functional activity may be controlled by a family of transcription factors known to be associated with the prevention of hypertrophy.

Conclusion

The systems-driven analysis reported here provides the basis for the identification of potentially novel biomarkers and understanding HF-related mechanisms in a more comprehensive and integrated way.

A potential tumor suppressor role for Hic1 in breast cancer through transcriptional repression of ephrin-A1

The tumor suppressor gene hypermethylated in cancer 1 (HIC1), which encodes a transcriptional repressor, is epigenetically inactivated in various human cancers. In this study, we show that HIC1 is a direct transcriptional repressor of the gene encoding ephrin-A1, a cell surface ligand implicated in the pathogenesis of epithelial cancers. We also show that mouse embryos lacking both Hic1 alleles manifest developmental defects spatially associated with the misexpression of ephrin-A1, and that overexpression of ephrin-A1 is a feature of tumors arising in Hic1 heterozygous mice in which the remaining wild-type allele is epigenetically silenced. In breast cancer, we find that ephrin-A1 expression is common in vivo, but that in cell culture, expression of the EphA receptors is predominant. Restoration of HIC1 function in breast cancer cells leads to a reduction in tumor growth in vivo, an effect that can be partially rescued by co-overexpression of ephrin-A1. Interestingly, overexpression of ephrin-A1 in vitro triggers downregulation of EphA2 and EphA4 levels, resulting in an expression pattern similar to that seen in vivo. We conclude that Hic1 spatially restricts ephrin-A1 expression in development, and that upregulated expression of ephrin-A1 resulting from epigenetic silencing of HIC1 in cancer cells may be an important mechanism in epithelial malignancy.

Estrogen receptor beta binds to and regulates three distinct classes of target genes

Estrogen receptor beta (ERbeta) has potent antiproliferative and anti-inflammatory properties, suggesting that ERbeta-selective agonists might be a new class of therapeutic and chemopreventive agents. To understand how ERbeta regulates genes, we identified genes regulated by the unliganded and liganded forms of ERalpha and ERbeta in U2OS cells. Microarray data demonstrated that virtually no gene regulation occurred with unliganded ERalpha, whereas many genes were regulated by estradiol (E(2)). These results demonstrated that ERalpha requires a ligand to regulate a single class of genes. In contrast, ERbeta regulated three classes of genes. Class I genes were regulated primarily by unliganded ERbeta. Class II genes were regulated only with E(2), whereas class III genes were regulated by both unliganded ERbeta and E(2). There were 453 class I genes, 258 class II genes, and 83 class III genes. To explore the mechanism whereby ERbeta regulates different classes of genes, chromatin immunoprecipitation-sequencing was performed to identify ERbeta binding sites and adjacent transcription factor motifs in regulated genes. AP1 binding sites were more enriched in class I genes, whereas ERE, NFkappaB1, and SP1 sites were more enriched in class II genes. ERbeta bound to all three classes of genes, demonstrating that ERbeta binding is not responsible for differential regulation of genes by unliganded and liganded ERbeta. The coactivator NCOA2 was differentially recruited to several target genes. Our findings indicate that the unliganded and liganded forms of ERbeta regulate three classes of genes by interacting with different transcription factors and coactivators.

Analysis of floral transcription factors from Lycoris longituba

Transcription factors (TFs) are proteins that bind to specific promoter regions of their target genes and regulate gene transcription. Many of these factors have been found to influence flowering. Lycoris longituba exhibits a great deal of diversity in flower color and flower form, making it a suitable model for the study of floral development. We have identified 338 putative TFs from more than thirty thousand ESTs sequenced from the floral tissue of L. longituba, and validated them using real-time RT-PCR. Fifty-one of the TFs were recognized as being potentially flower-specific, and the expression patterns of some of them during six flowering phases have been elucidated. Homolog annotation and phylogenetic analysis revealed that some TFs that belong to several TF families, such as MADS, MYB-related, NAC, and ABI3-VP1, were suggested to play important roles in the flowering process. Our dataset may be used to identify priority target TF genes for further study.

Liverbase: a comprehensive view of human liver biology

The Liverbase ( http://liverbase.hupo.org.cn ) integrates information on the human liver proteome, including the function, abundance, and subcellular localization of proteins as well as associated disease information. The overall objective of the Liverbase is to provide a unique public resource for the liver community by providing comprehensive functional annotation of proteins implicated in liver development and disease. The central database features are manually annotated proteins localized in or functionally associated with human liver. In this first version of Liverbase, the associated data includes the human liver proteome (6788 proteins) and transcriptome (11205 significantly expressed genes: 10224 from CHIP and 5422 from MPSS, respecively) from the Chinese human liver proteome project (CNHLPP). As a database made publicly available through the Web site, Liverbase provides browsing and searching capabilities and a compilation of external links to other databases and homepages. Liverbase enables (i) the establishment of liver GO slim with 51 nonredundant items; (ii) systematic searches for proteins within specific functional or metabolic pathways; (iii) systematic searches that aim to find the proteins that underlie common and rare liver diseases; and (iv) the integration of detailed protein annotations derived from the literature. Liverbase also contains an external links page with links to other biological databases and homepages, including GO, KEGG, pfam, SWISS-PROT, and GNF databases. Liverbase users can utilize all these information to conduct systems biology research on liver.

The four hexamerin genes in the honey bee: structure, molecular evolution and function deduced from expression patterns in queens, workers and drones

Background

Hexamerins are hemocyanin-derived proteins that have lost the ability to bind copper ions and transport oxygen; instead, they became storage proteins. The current study aimed to broaden our knowledge on the hexamerin genes found in the honey bee genome by exploring their structural characteristics, expression profiles, evolution, and functions in the life cycle of workers, drones and queens.

Results

The hexamerin genes of the honey bee (hex 70a, hex 70b, hex 70c and hex 110) diverge considerably in structure, so that the overall amino acid identity shared among their deduced protein subunits varies from 30 to 42%. Bioinformatics search for motifs in the respective upstream control regions (UCRs) revealed six overrepresented motifs including a potential binding site for Ultraspiracle (Usp), a target of juvenile hormone (JH). The expression of these genes was induced by topical application of JH on worker larvae. The four genes are highly transcribed by the larval fat body, although with significant differences in transcript levels, but only hex 110 and hex 70a are re-induced in the adult fat body in a caste- and sex-specific fashion, workers showing the highest expression. Transcripts for hex 110, hex 70a and hex70b were detected in developing ovaries and testes, and hex 110 was highly transcribed in the ovaries of egg-laying queens. A phylogenetic analysis revealed that HEX 110 is located at the most basal position among the holometabola hexamerins, and like HEX 70a and HEX 70c, it shares potential orthology relationship with hexamerins from other hymenopteran species.

Conclusions

Striking differences were found in the structure and developmental expression of the four hexamerin genes in the honey bee. The presence of a potential binding site for Usp in the respective 5' UCRs, and the results of experiments on JH level manipulation in vivo support the hypothesis of regulation by JH. Transcript levels and patterns in the fat body and gonads suggest that, in addition to their primary role in supplying amino acids for metamorphosis, hexamerins serve as storage proteins for gonad development, egg production, and to support foraging activity. A phylogenetic analysis including the four deduced hexamerins and related proteins revealed a complex pattern of evolution, with independent radiation in insect orders.

Inferring cluster-based networks from differently stimulated multiple time-course gene expression data

Motivation: Clustering and gene network inference often help to predict the biological functions of gene subsets. Recently, researchers have accumulated a large amount of time-course transcriptome data collected under different treatment conditions to understand the physiological states of cells in response to extracellular stimuli and to identify drug-responsive genes. Although a variety of statistical methods for clustering and inferring gene networks from expression profiles have been proposed, most of these are not tailored to simultaneously treat expression data collected under multiple stimulation conditions.

Results: We propose a new statistical method for analyzing temporal profiles under multiple experimental conditions. Our method simultaneously performs clustering of temporal expression profiles and inference of regulatory relationships among gene clusters. We applied this method to MCF7 human breast cancer cells treated with epidermal growth factor and heregulin which induce cellular proliferation and differentiation, respectively. The results showed that the method is useful for extracting biologically relevant information.

Availability: A MATLAB implementation of the method is available from http://csb.gsc.riken.jp/yshira/software/clusterNetwork.zip

Contact:yshira@riken.jp

Supplementary information:Supplementary data are available at Bioinformatics online.

Identification of common variants within KCNK17 in Chinese Han population

KCNK17 is a member of the acid-sensitive subfamily of tandem pore K(+) channels, which are open at all membrane potentials an red contribute to cellular resting membrane potential. Recent genome-wide study (GWA) has shown that variants within KCNK17 confer genetic susceptibility for increasing ischemic stroke. In an effort to discover additional polymorphism(s), we scrutinized the genetic polymorphisms in the KCNK17. By direct DNA sequencing in 32 individuals, we identified nine sequence variants within the 16 kb of whole KCNK17 gene: one in exon1, one in intron and seven in the promoter region. Haplotypes, their frequencies and linkage disequilibrium coefficients (D'), among polymorphisms were estimated. All the polymorphisms in the 5'-flanking region (SNP2-SNP7) being in complete (or nearly complete) association with each other in the promoter region maybe produce synergistic effect to regulate the expression of KCNK17 gene and then have an influence on the pathogenesis of cerebrovascular diseases. The common haplotypes were observed comprising 88.9% of the total haplotypes in the same block. Bioinformatic analysis predicted several potential transcriptional factors binding sites by SNP -95, -134, -596 and -846. However, these binding sites need to be experimentally verified. The information concerning genetic polymorphisms of KCNK17 gene might provide valuable information for future genetic studies of diseases.