BACKGROUND:Carcinogenesis occurs, at least in part, due to the accumulation of mutations in critical genes that control the mechanisms of cell proliferation, differentiation and death. Publicly accessible databases contain millions of expressed sequence tag (EST) and single nucleotide polymorphism (SNP) records, which have the potential to assist in the identification of SNPs overrepresented in tumor tissue.METHODS:An in silico SNP-tumor association study was performed utilizing tissue library and SNP information available in NCBI's dbEST (release 092002) and dbSNP (build 106).RESULTS:A total of 4865 SNPs were identified which were present at higher allele frequencies in tumor compared to normal tissues. A subset of 327 (6.7%) SNPs induce amino acid changes to the protein coding sequences. This approach identified several SNPs which have been previously associated with carcinogenesis, as well as a number of SNPs that now warrant further investigationCONCLUSIONS:This novel in silico approach can assist in prioritization of genes and SNPs in the effort to elucidate the genetic mechanisms underlying the development of cancer.

SUMMARYTo facilitate the designing process for vector-based siRNA and siRNA cassette, a tool set has been developed consisting of a siRNA target finder, a siRNA construct builder and a siRNA sequence scrambler. The siRNA target finder is used to identify candidate siRNA target sites. The program automates homology filtering, minimizes non-specific cross-reaction, filters target sites based on RNA duplex internal stability and siRNA sense/anti-sense strand secondary structure. The siRNA construct builder is used to create a siRNA hairpin construct as a vector insert or a cassette insert. The siRNA sequence scrambler is used to generate a negative control sequence for siRNA experiments. Together, these programs provide a comprehensive utility set to address the specific bioinformatics need of DNA-based siRNA design.AVAILABILITYThe Web-based design tools are available at GenScript Website (siRNA design center). http://www.genscript.com or http://www.genscript.com/rnai.html#design or http://www.genscript.com/sirna_ca.html#design

The completion of the human genome sequence and availability of cDNA microarray technology provide new approaches to explore global cellular regulatory mechanisms. Here we present a strategy to identify genes regulated by specific transcription factors in the human genome, and apply it to p53. We first collected promoters or introns of all genes available using two methods: GenBank annotation and a computationally derived transcript map. The "FindPatterns" program is then used to search sequences in regulatory regions that match the p53 DNA-binding consensus sequence, resulting in the p53 Target Database. This database collects human genes that have at least one p53 DNA-binding sequence in their regulatory region. cDNA microarray was also used to identify genes that respond to p53 at a genomic scale. Integration of the microarray data and the p53 Target Database should greatly enrich direct p53 target genes. Taqman analysis and quantitative chromatin immunoprecipitation analysis are used to validate the in silico prediction and microarray data. Enrichment factor analysis is used to demonstrate that in silico prediction greatly enriches for genes that are transcriptionally regulated by p53 and assists us to identify other signaling pathways that are potentially connected to p53. The approaches can be extended to other transcription factors. The methods shown here illustrate a novel approach to the analysis of global gene regulatory networks through the integration of human genomic sequence information and genome-wide gene expression analysis.

Dietary cholesterol consumption and intestinal cholesterol absorption contribute to plasma cholesterol levels, a risk factor for coronary heart disease. The molecular mechanism of sterol uptake from the lumen of the small intestine is poorly defined. We show that Niemann-Pick C1Like 1(NPC1L1) protein plays a critical role in the absorption of intestinal cholesterol. NPC1L1 expression is enriched in the small intestine and is in the brush border membrane of enterocytes. Although otherwise phenotypically normal, NPC1L1-deficient mice exhibit a substantial reduction in absorbed cholesterol, which is unaffected by dietary supplementation of bile acids. Ezetimibe, a drug that inhibits cholesterol absorption, had no effect in NPC1L1 knockout mice, suggesting that NPC1L1 resides in an ezetimibe-sensitive pathway responsible for intestinal cholesterol absorption.

MAPK (mitogen-activated protein kinase) pathways constitute major regulators of cellular transcriptional programmes. We analysed the ERK1,2 (extracellular-signal-regulated kinase 1,2) transcriptome in a non-transformed MEC (mammary epithelial cell) line, MCF-12A, utilizing rAd MEK1EE, a recombinant adenovirus encoding constitutively active MEK1 (MAPK/ERK kinase 1). rAd MEK1EE infection induced morphological changes and DNA synthesis which were inhibited by the MEK1,2 inhibitor PD184352. Hierarchical clustering of data derived from seven time points over 24 h identified 430 and 305 co-ordinately up-regulated and down-regulated genes respectively. c-Myc binding sites were identified in the promoters of most of these up-regulated genes. A total of 46 candidate effectors of the Raf/MEK/ERK1,2 pathway in MECs were identified by comparing our dataset with previously reported Raf-1-regulated genes. These analyses led to the identification of a suite of growth factors co-ordinately induced by MEK1EE, including multiple ErbB ligands, vascular endothelial growth factor and PHRP (parathyroid hormone-related protein). PHRP is the primary mediator of humoral hypercalcaemia of malignancy, and has been implicated in metastasis to bone. We demonstrate that PHRP is secreted by MEK1EE-expressing cells. This secretion is inhibited by PD184352, but not by ErbB inhibitors. Our results suggest that, in addition to anti-proliferative properties, MEK1,2 inhibitors may be anti-angiogenic and possess therapeutic utility in the treatment of PHRP-positive tumours.

Single nucleotide polymorphisms (SNPs) are linked to phenotypes associated with diseases and drug responses. Many techniques are now available to identify and quantify such SNPs in DNA or RNA pools, although the information on the latter is limited. The majority of these methodologies require prior knowledge of target sequences, normally obtained through DNA sequencing. Direct quantitation of SNPs from DNA sequencing raw data will save time and money for large amount sample analysis. A high throughput DNA sequencing assay, in combination with a SNP quantitative algorithm, was developed for the quantitation of a SNP present in HCV RNA sequences. For a side-by-side comparison, a Pyrosequencing assay was also developed. Quantitation performance was evaluated for both methods. The direct DNA sequencing quantitation method was shown to be more linear, accurate, sensitive, and reproducible than the Pyrosequencing method for the quantitation of the SNP present in HCV RNA molecules.

Orphan G-protein-coupled receptors are a large class of receptors whose cognate ligands are unknown. SP9155 (also referred to as AQ27 and GPR103) is an orphan G-protein-coupled receptor originally cloned from a human brain cDNA library. SP9155 was found to be predominantly expressed in brain, heart, kidney, retina, and testis. Phylogenetic analysis shows that SP9155 shares high homology with Orexin, NPFF, and cholecystokinin (CCK) receptors, but identification of the endogenous ligand for SP9155 has not been reported. In this study, we have used a novel method to predict peptides from genome data bases. From these predicted peptides, a novel RF-amide peptide, P52 was shown to selectively activate SP9155-transfected cells. We subsequently cloned the precursor gene of the P52 ligand and characterized the activity of other possible peptides encoded by the precursor. This revealed an extended peptide, P518, which exhibited high affinity for SP9155 (EC50 = 7 nm). mRNA expression analysis revealed that the peptide P518 precursor gene is predominantly expressed in various brain regions, coronary arteries, thyroid and parathyroid glands, large intestine, colon, bladder, testes, and prostate. These results indicate the existence of a novel RF-amide neuroendocrine peptide system, and suggest that SP9155 is likely the relevant G-protein-coupled receptor for this peptide.

The transcription factor Myc is induced by mitogenic signals and regulates downstream cellular responses. If overexpressed, Myc promotes malignant transformation. Myc modulates expression of diverse genes in experimental systems, but few are proven direct targets. Here, we present a large-scale screen for genomic Myc-binding sites in live human cells. We used bioinformatics to select consensus DNA elements (CACGTG or E-boxes) situated in the 5' regulatory region of genes and measured Myc binding to those sequences in vivo by quantitative chromatin immunoprecipitation. Strikingly, most promoter-associated E-boxes showed selective recovery with Myc, unlike non-E-box promoters or E-boxes in bulk genomic DNA. Promoter E-boxes were distributed in two groups bound by Myc at distinct frequencies. The high-affinity group included an estimated 11% of all cellular loci, was highly conserved among different cells, and was bound independently of Myc expression levels. Overexpressed Myc associated at increased frequency with low-affinity targets and, at extreme levels, also with other sequences, suggesting that some binding was not sequence-specific. The strongest DNA-sequence parameter defining high-affinity targets was the location of E-boxes within CpG islands, correlating with an open, preacetylated state of chromatin. Myc further enhanced histone acetylation, with or without accompanying induction of mRNA expression. Our findings point to a high regulatory and biological diversity among Myc-target genes.

The temporal gene expression profile during the entire process of apoptosis and cell cycle progression in response to p53 in human ovarian cancer cells was explored with cDNA microarrays representing 33 615 individual human genes. A total of 1501 genes (4.4%) were found to respond to p53 (approximately 80% of these were repressed by p53) using 2.5-fold change as a cutoff. It was anticipated that most of p53 responsive genes resulted from the secondary effect of p53 expression at late stage of apoptosis. To delineate potential p53 direct and indirect target genes during the process of apoptosis and cell cycle progression, microarray data were combined with global p53 DNA-binding site analysis. Here we showed that 361 out of 1501 p53 responsive genes contained p53 consensus DNA-binding sequence(s) in their regulatory region, approximately 80% of which were repressed by p53. This is the first time that a large number of p53-repressed genes have been identified to contain p53 consensus DNA-binding sequence(s) in their regulatory region. Hierarchical cluster analysis of these genes revealed distinct temporal expression patterns of transcriptional activation and repression by p53. More genes were activated at early time points, while more repressed genes were found after the onset of apoptosis. A small-scale quantitative chromatin immunoprecipitation analysis indicated that in vivo p53-DNA interaction was detected in eight out of 10 genes, most of which were repressed by p53 at the early onset of apoptosis, suggesting that a portion of p53 target genes in the human genome could be negatively regulated by p53 via sequence-specific DNA binding. The approaches and genes described here should aid the understanding of global gene regulatory network of p53.

Gene expression profiles and transcription factors involved in PTH signaling in osteoblasts revealed by microarray and bioinformatics Ling Qin, Ping Qiu, Luquan Wang, Xin Li, John T Swarthout, Patricia Soteropoulos, Peter Tolias and Nicola C Partridge Department of Physiology and Biophysics, UMDNJ-Robert Wood Johnson Medical School, Piscataway, NJ; Schering-Plough Research Institute, Kenilworth, NJ; Center for Applied Genomics, Public Health Research Institute and Department of Microbiology and Molecular Genetics, UMDNJ-New Jersey Medical School, Newark, NJ. current address: Department of Cell Biology and Physiology, Washington University School of Medicine, Saint Louis, MO; Correspondence to: Nicola C Partridge, Department of Physiology and Biophysics, UMDNJ-Robert Wood Johnson Medical School, 675 Hoes Lane, Piscataway, NJ 08854. Tel: 732-2354617; Fax: 732-2355038; Email: partrinc@umdnj.edu Abbreviations: PTH, parathyroid hormone; AP-1, activator protein-1; CREB, cAMPresponse-element-binding-protein; C/EBP, CCAAT/enhancer binding protein. Running title: Genes regulated by PTH in osteoblasts

Taking advantage of the “working draft” of the human genome and the MIT shotgun assembly of the mouse genome, we performed a comparative promoter analysis of human RefSeq mRNA (sequences from GenBank's RefSeq database). By combining this analysis with a transcription factor (TF) binding site analysis using a TRANSFAC position weight matrix (PWM) search, 86% of non-specific TF sites were removed. Using a set of genes that are regulated by parathyroid hormone (PTH), a statistical analysis was performed on the conserved TF binding sites among a set of eight human and mouse genes. From among the eight genes tested, we obtained a set of 31 TFs, suggesting possible roles for associated genes in PTH-mediated pathways. All three known PTH-responsive TFs (AP1, RUNX2, CREB) were correctly predicted by this analysis as well as two other potential TFs (VDR and CEBPDelta). Additionally, a model was made to describe the TF site characteristic module of PTH-regulated genes. This model was then used to search all human RefSeq gene promoters with established human–mouse ortholog relationships to identify other PTH-regulated genes. This comparative approach combined with statistical analysis proved to be sufficiently specific to decipher critical TFs involved in PTH-regulated pathways.

Parathyroid hormone (PTH) binds to its receptor PTH1R ( parathyroid hormone 1 receptor) in osteoblastic cells to regulate bone remodeling and calcium homeostasis. While prolonged exposure to PTH causes increased bone resorption, intermittent injections of PTH have an anabolic effect on bone. The molecular mechanisms regulating these processes are still largely unknown. Here, we present our results on gene expression profile changes in the PTH-treated osteoblastic cell line, UMR 106-01, using DNA microarray analysis. A total of 125 known genes and 30 unknown expressed sequence tags ( ESTs) were found to have at least 2-fold expression changes after PTH treatment at 4, 12, and 24 h. 14 genes were previously known to be PTH-regulated but many were unknown to be regulated by PTH prior to our experiments. Real-time reverse transcriptase-PCR confirmed that 90 and 50% of the genes are regulated more than 2-fold by PTH in UMR 106-01 and rat primary osteoblastic cells, respectively. Most genes belong to the following protein families: hormones, growth factors, and receptors; signal transduction pathway proteins; transcription factors; proteases; metabolic enzymes; structural and matrix proteins; transporters; etc. These results provide a comprehensive and deeper knowledge about PTH regulation of osteoblastic gene expression. Next, we designed a computational method to extract information about transcription factors likely involved in regulating these genes. These factors include those previously known to be involved in PTH signaling (AP-1 and the cAMP response element-binding protein), those that were identified by microarray data (C/EBP), and some novel transcription factors ( AP-2, AP-4, SP1, FoxD3, etc.). Our results suggest that a reliable bioinformatics approach can be easily applied for other systems.

In this study we used adenovirus vector-mediated transduction of either the p53 gene (rAd-p53) or the p21(WAF1/CIP1) gene (rAd-p21) to mimic both p53-dependent and -independent up-regulation of p21(WAF1/CIP1) within a human ovarian cancer cell line, 2774, and the derivative cell lines, 2774qw1 and 2774qw2. We observed that rAd-p53 can induce apoptosis in both 2774 and 2774qw1 cells but not in 2774qw2 cells. Surprisingly, overexpression of p21(WAF1/CIP1) also triggered apoptosis within these two cell lines. Quantitative reverse transcription-PCR analysis revealed that the differential expression of BAX, BCL2, and caspase 3 genes, specific in rAd-p53-induced apoptotic cells, was not altered in rAd-p21-induced apoptotic cells, suggesting p21(WAF1/CIP1)-induced apoptosis through a pathway distinguishable from p53-induced apoptosis. Expression analysis of 2774qw1 cells infected with rAd-p21 on 60,000 cDNA microarrays identified 159 genes in response to p21(WAF1/CIP1) expression in at least one time point with 2.5-fold change as a cutoff. Integration of the data with the parallel microarray experiments with rAd-p53 infection allowed us to extract 66 genes downstream of both p53 and p21(WAF1/CIP1) and 93 genes in response to p21(WAF1/CIP1) expression in a p53-independent pathway. The genes in the former set may play a dual role in both p53-dependent and p53-independent pathways, and the genes in the latter set gave a mechanistic molecular explanation for p53-independent p21(WAF1/CIP1)-induced apoptosis. Furthermore, promoter sequence analysis suggested that transcription factor E2F family is partially responsible for the differential expression of genes following p21(WAF1/CIP1). This study has profound significance toward understanding the role of p21(WAF1/CIP1) in p53-independent apoptosis.

A new lactone compound named cannabifolactone A was isolated from the water extract of the aerial parts of Senecio cannabifolius Less. Its structure was elucidated mainly by 1D- and 2D-NMR techniques.

Tumors evade cell death by constitutively activating cell survival pathways and suppressing intrinsic death machinery. Activation of cell survival pathways leads to transcriptional repression of genes associated with cell death and activation of ones promoting anti-apoptosis. Akt/protein kinase B phosphorylates forkhead transcription factors and prevents their nuclear localization, leading to repression of genes involved in apoptosis, such as Fas ligand (FasL). Using bioinformatic approaches, we have identified three consensus sequences for forkhead transcription factor binding in transforming growth factor β2 (TGF-β2) promoter. TGF-β inhibits cell proliferation and induces apoptosis in many cell types, and acquisition of TGF-β resistance is linked to tumorigenesis. In this study, we show that activated Akt down-regulates TGF-β2 promoter, and sequences within the promoter that are related to consensus forkhead binding sites are necessary for repression. Forkhead factor FKHRL1 binds in vitro to the three consensus sequences and can activate TGF-β2 promoter in normal and Akt-transformed cell lines. In human breast and pancreatic tumors, activated Akt expression correlated with down-regulation of TGF-β 2 mRNA levels. A number of tumor cells expressing activated Akt were responsive to TGF-β addition, indicating the presence of an intact TGF-β-signaling pathway. These results suggest that repression of TGF-β 2 promoter activity in cells expressing activated Akt may play a role in promoting tumorigenesis and escape from the growth-inhibitory and/or apoptotic effects of TGF-β.

The iron response element (IRE) is a highly conserved RNA stem loop structure. It is the binding site of iron regulatory protein (IRP). IRP binding to IRE is regulated by cellular iron. When cells are derived of iron, IRP binds IRE. If IRE is located at 5'UTR, IRP binding will inhibit translation initiation, else if IRE is at 3'UTR, IRP binding will stabilize mRNA and prevent it from degradation. So far all known IREs have C at the 1 position and G at the 5 position of the loop (C1G5 type). In vitro studies suggest that the U1A5 type IRE, which has U and A at the 1 and 5 loop position respectively, binds well to IRP. However, U1A5 type's in vivo existence is still elusive. IRE-IRP binding is involved in the regulation of iron metabolism, oxidative stress and possibly aging. Here we use an improved computation method performing a comprehensive search of IRE in human and mouse genes. We try to catalog potential human and mouse IRE containing genes, at the same time identify potential U1A5 IREs.

BACKGROUND:Inhalation of Ascaris suum antigen by allergic monkeys causes an immediate bronchoconstriction and delayed allergic reaction, including a pulmonary inflammatory infiltrate. To identify genes involved in this process, the gene-expression pattern of allergic monkey lungs was profiled by microarrays. Monkeys were challenged by inhalation of A. suum antigen or given interleukin-4 (IL-4) treatment; lung tissue was collected at 4, 18 or 24 h after antigen challenge or 24 h after IL-4. Each challenged monkey lung was compared to a pool of normal, unchallenged monkey lungs.RESULTS:Of the approximately 40,000 cDNAs represented on the microarray, expression levels of 169 changed by more than 2.5-fold in at least one of the pairwise probe comparisons; these cDNAs encoded 149 genes, of which two thirds are known genes. The largest number of regulated genes was observed 4 h after challenge. Confirmation of differential expression in the original tissue was obtained for 95% of a set of these genes using real-time PCR. Cluster analysis revealed at least five groups of genes with unique expression patterns. One cluster contained genes for several chemokine mediators including eotaxin, PARC, MCP-1 and MCP-3. Genes involved in tissue remodeling and antioxidant responses were also identified as regulated by antigen and IL-4 or by antigen only.CONCLUSION:This study provides a large-scale profile of gene expression in the primate lung following allergen or IL-4 challenge. It shows that microarrays, with real-time PCR, are a powerful tool for identifying and validating differentially expressed genes in a disease model.

BACKGROUND:Co-regulation of genes may imply involvement in similar biological processes or related function. Many clusters of co-regulated genes have been identified using microarray experiments. In this study, we examined co-regulated gene families using large-scale cDNA microarray experiments on the human transcriptome.RESULTS:We present a simple model, which, for each probe pair, distills expression changes into binary digits and summarizes the expression of multiple members of a gene family as the Family Regulation Ratio. The set of Family Regulation Ratios for each protein family across multiple experiments is called a Family Regulation Profile. We analyzed these Family Regulation Profiles using Pearson Correlation Coefficients and derived a network diagram portraying relationships between the Family Regulation Profiles of gene families that are well represented on the microarrays. Our strategy was cross-validated with two randomly chosen data subsets and was proven to be a reliable approach.CONCLUSION:This work will help us to understand and identify the functional relationships between gene families and the regulatory pathways in which each family is involved. Concepts presented here may be useful for objective clustering of protein functions and deriving a comprehensive protein interaction map. Functional genomic approaches such as this may also be applicable to the elucidation of complex genetic regulatory networks.

INTRODUCTION. Complex differential expression of genes in higher organisms is achieved through combinatorial regulation of transcription by specific combination of transcription factors binding to their target sites in the regulatory regions of these genes. The composite elements (CE) model was defined as pairs of closely situated binding sites, corresponding transcription factors, protein–protein interaction between them, and expression patterns provided by this combinatorial regulation[1]. In this study, we describe a novel computational approach to detect possible composite elements in genomic sequence. The method is based on the detection of overrepresented adjacent transcription binding sites.