Search

Alternate promoter usage is an important molecular mechanism for generating RNA and protein diversity. Cap Analysis Gene Expression (CAGE) is a powerful approach for revealing the multiplicity of transcription start site (TSS) events across experiments and conditions. An understanding of the dynamics of TSS choice across these conditions requires both sensitive quantification and comparative visualization. We have developed CAGExploreR, an R package to detect and visualize changes in the use of specific TSS in wider promoter regions in the context of changes in overall gene expression when comparing different CAGE samples. These changes provide insight into the modification of transcript isoform generation and regulatory network alterations associated with cell types and conditions. CAGExploreR is based on the FANTOM5 and MPromDb promoter set definitions but can also work with user-supplied regions. The package compares multiple CAGE libraries simultaneously. Supplementary Materials describe methods in detail, and a vignette demonstrates a workflow with a real data example., Availability and Implementation: The package is freely available under the MIT license from CRAN (http://cran.r-project.org/web/packages/CAGExploreR)., Contact: edimont@mail.harvard.edu Supplementary information: Supplementary data are available at Bioinformatics online., (© The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)

Regulated transcription controls the diversity, developmental pathways and spatial organization of the hundreds of cell types that make up a mammal. Using single-molecule cDNA sequencing, we mapped transcription start sites (TSSs) and their usage in human and mouse primary cells, cell lines and tissues to produce a comprehensive overview of mammalian gene expression across the human body. We find that few genes are truly 'housekeeping', whereas many mammalian promoters are composite entities composed of several closely separated TSSs, with independent cell-type-specific expression profiles. TSSs specific to different cell types evolve at different rates, whereas promoters of broadly expressed genes are the most conserved. Promoter-based expression analysis reveals key transcription factors defining cell states and links them to binding-site motifs. The functions of identified novel transcripts can be predicted by coexpression and sample ontology enrichment analyses. The functional annotation of the mammalian genome 5 (FANTOM5) project provides comprehensive expression profiles and functional annotation of mammalian cell-type-specific transcriptomes with wide applications in biomedical research.

Background: The impact of raltegravir-resistant HIV-1 minority variants (MVs) on raltegravir treatment failure is unknown. Illumina sequencing offers greater throughput than 454, but sequence analysis tools for viral sequencing are needed. We evaluated Illumina and 454 for the detection of HIV-1 raltegravir-resistant MVs., Methods: A5262 was a single-arm study of raltegravir and darunavir/ritonavir in treatment-naïve patients. Pre-treatment plasma was obtained from 5 participants with raltegravir resistance at the time of virologic failure. A control library was created by pooling integrase clones at predefined proportions. Multiplexed sequencing was performed with Illumina and 454 platforms at comparable costs. Illumina sequence analysis was performed with the novel snp-assess tool and 454 sequencing was analyzed with V-Phaser., Results: Illumina sequencing resulted in significantly higher sequence coverage and a 0.095% limit of detection. Illumina accurately detected all MVs in the control library at ≥0.5% and 7/10 MVs expected at 0.1%. 454 sequencing failed to detect any MVs at 0.1% with 5 false positive calls. For MVs detected in the patient samples by both 454 and Illumina, the correlation in the detected variant frequencies was high (R2 = 0.92, P<0.001). Illumina sequencing detected 2.4-fold greater nucleotide MVs and 2.9-fold greater amino acid MVs compared to 454. The only raltegravir-resistant MV detected was an E138K mutation in one participant by Illumina sequencing, but not by 454., Conclusions: In participants of A5262 with raltegravir resistance at virologic failure, baseline raltegravir-resistant MVs were rarely detected. At comparable costs to 454 sequencing, Illumina demonstrated greater depth of coverage, increased sensitivity for detecting HIV MVs, and fewer false positive variant calls.

Clinical adoption of human genome sequencing requires methods that output genotypes with known accuracy at millions or billions of positions across a genome. Because of substantial discordance among calls made by existing sequencing methods and algorithms, there is a need for a highly accurate set of genotypes across a genome that can be used as a benchmark. Here we present methods to make high-confidence, single-nucleotide polymorphism (SNP), indel and homozygous reference genotype calls for NA12878, the pilot genome for the Genome in a Bottle Consortium. We minimize bias toward any method by integrating and arbitrating between 14 data sets from five sequencing technologies, seven read mappers and three variant callers. We identify regions for which no confident genotype call could be made, and classify them into different categories based on reasons for uncertainty. Our genotype calls are publicly available on the Genome Comparison and Analytic Testing website to enable real-time benchmarking of any method.

The initiation of cellular programs is orchestrated by key transcription factors and chromatin regulators that activate or inhibit target gene expression. To generate a compendium of chromatin factors that establish the epigenetic code during developmental haematopoiesis, a large-scale reverse genetic screen was conducted targeting orthologues of 425 human chromatin factors in zebrafish. A set of chromatin regulators was identified that target different stages of primitive and definitive blood formation, including factors not previously implicated in haematopoiesis. We identified 15 factors that regulate development of primitive erythroid progenitors and 29 factors that regulate development of definitive haematopoietic stem and progenitor cells. These chromatin factors are associated with SWI/SNF and ISWI chromatin remodelling, SET1 methyltransferase, CBP-p300-HBO1-NuA4 acetyltransferase, HDAC-NuRD deacetylase, and Polycomb repressive complexes. Our work provides a comprehensive view of how specific chromatin factors and their associated complexes play a major role in the establishment of haematopoietic cells in vivo.

PROM1 is the gene encoding prominin-1 or CD133, an important cell surface marker for the isolation of both normal and cancer stem cells. PROM1 transcripts initiate at a range of transcription start sites (TSS) associated with distinct tissue and cancer expression profiles. Using high resolution Cap Analysis of Gene Expression (CAGE) sequencing we characterize TSS utilization across a broad range of normal and developmental tissues. We identify a novel proximal promoter (P6) within CD133(+) melanoma cell lines and stem cells. Additional exon array sampling finds P6 to be active in populations enriched for mesenchyme, neural stem cells and within CD133(+) enriched Ewing sarcomas. The P6 promoter is enriched with respect to previously characterized PROM1 promoters for a HMGI/Y (HMGA1) family transcription factor binding site motif and exhibits different epigenetic modifications relative to the canonical promoter region of PROM1.

Glioblastoma is the most common brain tumor. Median survival in unselected patients is <10 months. The tumor harbors stem-like cells that self-renew and propagate upon serial transplantation in mice, although the clinical relevance of these cells has not been well documented. We have performed the first genome-wide analysis that directly relates the gene expression profile of nine enriched populations of glioblastoma stem cells (GSCs) to five identically isolated and cultivated populations of stem cells from the normal adult human brain. Although the two cell types share common stem- and lineage-related markers, GSCs show a more heterogeneous gene expression. We identified a number of pathways that are dysregulated in GSCs. A subset of these pathways has previously been identified in leukemic stem cells, suggesting that cancer stem cells of different origin may have common features. Genes upregulated in GSCs were also highly expressed in embryonic and induced pluripotent stem cells. We found that canonical Wnt-signaling plays an important role in GSCs, but not in adult human neural stem cells. As well we identified a 30-gene signature highly overexpressed in GSCs. The expression of these signature genes correlates with clinical outcome and demonstrates the clinical relevance of GSCs., (Copyright © 2013 The Authors. Published by Elsevier Inc. All rights reserved.)

Basal-like triple-negative breast cancers (TNBCs) have poor prognosis. To identify basal-like TNBC dependencies, a genome-wide siRNA lethality screen compared two human breast epithelial cell lines transformed with the same genes: basal-like BPLER and myoepithelial HMLER. Expression of the screen's 154 BPLER dependency genes correlated with poor prognosis in breast, but not lung or colon, cancer. Proteasome genes were overrepresented hits. Basal-like TNBC lines were selectively sensitive to proteasome inhibitor drugs relative to normal epithelial, luminal, and mesenchymal TNBC lines. Proteasome inhibition reduced growth of established basal-like TNBC tumors in mice and blocked tumor-initiating cell function and macrometastasis. Proteasome addiction in basal-like TNBCs was mediated by NOXA and linked to MCL-1 dependence., (Copyright © 2013 Elsevier Inc. All rights reserved.)

Rationale: Endotoxin is a near ubiquitous environmental exposure that that has been associated with both asthma and chronic obstructive pulmonary disease (COPD). These obstructive lung diseases have a complex pathophysiology, making them difficult to study comprehensively in the context of endotoxin. Genome-wide gene expression studies have been used to identify a molecular snapshot of the response to environmental exposures. Identification of differentially expressed genes shared across all published murine models of chronic inhaled endotoxin will provide insight into the biology underlying endotoxin-associated lung disease., Methods: We identified three published murine models with gene expression profiling after repeated low-dose inhaled endotoxin. All array data from these experiments were re-analyzed, annotated consistently, and tested for shared genes found to be differentially expressed. Additional functional comparison was conducted by testing for significant enrichment of differentially expressed genes in known pathways. The importance of this gene signature in smoking-related lung disease was assessed using hierarchical clustering in an independent experiment where mice were exposed to endotoxin, smoke, and endotoxin plus smoke., Results: A 101-gene signature was detected in three murine models, more than expected by chance. The three model systems exhibit additional similarity beyond shared genes when compared at the pathway level, with increasing enrichment of inflammatory pathways associated with longer duration of endotoxin exposure. Genes and pathways important in both asthma and COPD were shared across all endotoxin models. Mice exposed to endotoxin, smoke, and smoke plus endotoxin were accurately classified with the endotoxin gene signature., Conclusions: Despite the differences in laboratory, duration of exposure, and strain of mouse used in three experimental models of chronic inhaled endotoxin, surprising similarities in gene expression were observed. The endotoxin component of tobacco smoke may play an important role in disease development.

Comparisons of stem cell experiments at both molecular and semantic levels remain challenging due to inconsistencies in results, data formats, and descriptions among biomedical research discoveries. The Harvard Stem Cell Institute (HSCI) has created the Stem Cell Commons (stemcellcommons.org), an open, community-based approach to data sharing. Experimental information is integrated using the Investigation-Study-Assay tabular format (ISA-Tab) used by over 30 organizations (ISA Commons, isacommons.org). The early adoption of this format permitted the novel integration of three independent systems to facilitate stem cell data storage, exchange and analysis: the Blood Genomics Repository, the Stem Cell Discovery Engine, and the new Refinery platform that links the Galaxy analytical engine to data repositories.

It is acknowledged that some obesity trajectories are set early in life, and that rapid weight gain in infancy is a risk factor for later development of obesity. Identifying modifiable factors associated with early rapid weight gain is a prerequisite for curtailing the growing worldwide obesity epidemic. Recently, much attention has been given to findings indicating that gut microbiota may play a role in obesity development. We aim at identifying how the development of early gut microbiota is associated with expected infant growth. We developed a novel procedure that allows for the identification of longitudinal gut microbiota patterns (corresponding to the gut ecosystem developing), which are associated with an outcome of interest, while appropriately controlling for the false discovery rate. Our method identified developmental pathways of Staphylococcus species and Escherichia coli that were associated with expected growth, and traditional methods indicated that the detection of Bacteroides species at day 30 was associated with growth. Our method should have wide future applicability for studying gut microbiota, and is particularly important for translational considerations, as it is critical to understand the timing of microbiome transitions prior to attempting to manipulate gut microbiota in early life.

Little is known about the mechanisms of persistent airflow obstruction that result from chronic occupational endotoxin exposure. We sought to analyze the inflammatory response underlying persistent airflow obstruction as a result of chronic occupational endotoxin exposure. We developed a murine model of daily inhaled endotoxin for periods of 5 days to 8 weeks. We analyzed physiologic lung dysfunction, lung histology, bronchoalveolar lavage fluid and total lung homogenate inflammatory cell and cytokine profiles, and pulmonary gene expression profiles. We observed an increase in airway hyperresponsiveness as a result of chronic endotoxin exposure. After 8 weeks, the mice exhibited an increase in bronchoalveolar lavage and lung neutrophils that correlated with an increase in proinflammatory cytokines. Detailed analyses of inflammatory cell subsets revealed an expansion of dendritic cells (DCs), and in particular, proinflammatory DCs, with a reduced percentage of macrophages. Gene expression profiling revealed the up-regulation of a panel of genes that was consistent with DC recruitment, and lung histology revealed an accumulation of DCs in inflammatory aggregates around the airways in 8-week-exposed animals. Repeated, low-dose LPS inhalation, which mirrors occupational exposure, resulted in airway hyperresponsiveness, associated with a failure to resolve the proinflammatory response, an inverted macrophage to DC ratio, and a significant rise in the inflammatory DC population. These findings point to a novel underlying mechanism of airflow obstruction as a result of occupational LPS exposure, and suggest molecular and cellular targets for therapeutic development.

Background: Animal studies suggest that early-life lead exposure influences gene expression and production of proteins associated with Alzheimer's disease (AD)., Objectives: We attempted to assess the relationship between early-life lead exposure and potential biomarkers for AD among young men and women. We also attempted to assess whether early-life lead exposure was associated with changes in expression of AD-related genes., Methods: We used sandwich enzyme-linked immunosorbent assays (ELISA) to measure plasma concentrations of amyloid β proteins Aβ40 and Aβ42 among 55 adults who had participated as newborns and young children in a prospective cohort study of the effects of lead exposure on development. We used RNA microarray techniques to analyze gene expression., Results: Mean plasma Aβ42 concentrations were lower among 13 participants with high umbilical cord blood lead concentrations (≥ 10 μg/dL) than in 42 participants with lower cord blood lead concentrations (p = 0.08). Among 10 participants with high prenatal lead exposure, we found evidence of an inverse relationship between umbilical cord lead concentration and expression of ADAM metallopeptidase domain 9 (ADAM9), reticulon 4 (RTN4), and low-density lipoprotein receptor-related protein associated protein 1 (LRPAP1) genes, whose products are believed to affect Aβ production and deposition. Gene network analysis suggested enrichment in gene sets involved in nerve growth and general cell development., Conclusions: Data from our exploratory study suggest that prenatal lead exposure may influence Aβ-related biological pathways that have been implicated in AD onset. Gene network analysis identified further candidates to study the mechanisms of developmental lead neurotoxicity.

Background & Aims: The precise mechanisms by which IFN exerts its antiviral effect against HCV have not yet been elucidated. We sought to identify host genes that mediate the antiviral effect of IFN-α by conducting a whole-genome siRNA library screen., Methods: High throughput screening was performed using an HCV genotype 1b replicon, pRep-Feo. Those pools with replicate robust Z scores ≥2.0 entered secondary validation in full-length OR6 replicon cells. Huh7.5.1 cells infected with JFH1 were then used to validate the rescue efficacy of selected genes for HCV replication under IFN-α treatment., Results: We identified and confirmed 93 human genes involved in the IFN-α anti-HCV effect using a whole-genome siRNA library. Gene ontology analysis revealed that mRNA processing (23 genes, p=2.756e-22), translation initiation (nine genes, p=2.42e-6), and IFN signaling (five genes, p=1.00e-3) were the most enriched functional groups. Nine genes were components of U4/U6.U5 tri-snRNP. We confirmed that silencing squamous cell carcinoma antigen recognized by T cells (SART1), a specific factor of tri-snRNP, abrogates IFN-α's suppressive effects against HCV in both replicon cells and JFH1 infectious cells. We further found that SART1 was not IFN-α inducible, and its anti-HCV effector in the JFH1 infectious model was through regulation of interferon stimulated genes (ISGs) with or without IFN-α., Conclusions: We identified 93 genes that mediate the anti-HCV effect of IFN-α through genome-wide siRNA screening; 23 and nine genes were involved in mRNA processing and translation initiation, respectively. These findings reveal an unexpected role for mRNA processing in generation of the antiviral state, and suggest a new avenue for therapeutic development in HCV., (Copyright © 2011 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved.)

To make full use of research data, the bioscience community needs to adopt technologies and reward mechanisms that support interoperability and promote the growth of an open 'data commoning' culture. Here we describe the prerequisites for data commoning and present an established and growing ecosystem of solutions using the shared 'Investigation-Study-Assay' framework to support that vision.

Mounting evidence suggests that malignant tumors are initiated and maintained by a subpopulation of cancerous cells with biological properties similar to those of normal stem cells. However, descriptions of stem-like gene and pathway signatures in cancers are inconsistent across experimental systems. Driven by a need to improve our understanding of molecular processes that are common and unique across cancer stem cells (CSCs), we have developed the Stem Cell Discovery Engine (SCDE)-an online database of curated CSC experiments coupled to the Galaxy analytical framework. The SCDE allows users to consistently describe, share and compare CSC data at the gene and pathway level. Our initial focus has been on carefully curating tissue and cancer stem cell-related experiments from blood, intestine and brain to create a high quality resource containing 53 public studies and 1098 assays. The experimental information is captured and stored in the multi-omics Investigation/Study/Assay (ISA-Tab) format and can be queried in the data repository. A linked Galaxy framework provides a comprehensive, flexible environment populated with novel tools for gene list comparisons against molecular signatures in GeneSigDB and MSigDB, curated experiments in the SCDE and pathways in WikiPathways. The SCDE is available at http://discovery.hsci.harvard.edu.

Gene expression quantitative trait loci (eQTL) are useful for identifying single nucleotide polymorphisms (SNPs) associated with diseases. At times, a genetic variant may be associated with a master regulator involved in the manifestation of a disease. The downstream target genes of the master regulator are typically co-expressed and share biological function. Therefore, it is practical to screen for eQTLs by identifying SNPs associated with the targets of a transcript-regulator (TR). We used a multivariate regression with the gene expression of known targets of TRs and SNPs to identify TReQTLs in European (CEU) and African (YRI) HapMap populations. A nominal p-value of <1×10(-6) revealed 234 SNPs in CEU and 154 in YRI as TReQTLs. These represent 36 independent (tag) SNPs in CEU and 39 in YRI affecting the downstream targets of 25 and 36 TRs respectively. At a false discovery rate (FDR) = 45%, one cis-acting tag SNP (within 1 kb of a gene) in each population was identified as a TReQTL. In CEU, the SNP (rs16858621) in Pcnxl2 was found to be associated with the genes regulated by CREM whereas in YRI, the SNP (rs16909324) was linked to the targets of miRNA hsa-miR-125a. To infer the pathways that regulate expression, we ranked TReQTLs by connectivity within the structure of biological process subtrees. One TReQTL SNP (rs3790904) in CEU maps to Lphn2 and is associated (nominal p-value = 8.1×10(-7)) with the targets of the X-linked breast cancer suppressor Foxp3. The structure of the biological process subtree and a gene interaction network of the TReQTL revealed that tumor necrosis factor, NF-kappaB and variants in G-protein coupled receptors signaling may play a central role as communicators in Foxp3 functional regulation. The potential pleiotropic effect of the Foxp3 TReQTLs was gleaned from integrating mRNA-Seq data and SNP-set enrichment into the analysis.

Complex diseases result from contributions of multiple genes that act in concert through pathways. Here we present a method to prioritize novel candidates of disease-susceptibility genes depending on the biological similarities to the known disease-related genes. The extent of disease-susceptibility of a gene is prioritized by analyzing seven features of human genes captured in H-InvDB. Taking rheumatoid arthritis (RA) and prostate cancer (PC) as two examples, we evaluated the efficiency of our method. Highly scored genes obtained included TNFSF12 and OSM as candidate disease genes for RA and PC, respectively. Subsequent characterization of these genes based upon an extensive literature survey reinforced the validity of these highly scored genes as possible disease-susceptibility genes. Our approach, Prioritization ANalysis of Disease Association (PANDA), is an efficient and cost-effective method to narrow down a large set of genes into smaller subsets that are most likely to be involved in the disease pathogenesis., (Copyright © 2011. Published by Elsevier Inc.)

A simple biochemical method to isolate mRNAs pulled down with a transfected, biotinylated microRNA was used to identify direct target genes of miR-34a, a tumor suppressor gene. The method reidentified most of the known miR-34a regulated genes expressed in K562 and HCT116 cancer cell lines. Transcripts for 982 genes were enriched in the pull-down with miR-34a in both cell lines. Despite this large number, validation experiments suggested that ~90% of the genes identified in both cell lines can be directly regulated by miR-34a. Thus miR-34a is capable of regulating hundreds of genes. The transcripts pulled down with miR-34a were highly enriched for their roles in growth factor signaling and cell cycle progression. These genes form a dense network of interacting gene products that regulate multiple signal transduction pathways that orchestrate the proliferative response to external growth stimuli. Multiple candidate miR-34a-regulated genes participate in RAS-RAF-MAPK signaling. Ectopic miR-34a expression reduced basal ERK and AKT phosphorylation and enhanced sensitivity to serum growth factor withdrawal, while cells genetically deficient in miR-34a were less sensitive. Fourteen new direct targets of miR-34a were experimentally validated, including genes that participate in growth factor signaling (ARAF and PIK3R2) as well as genes that regulate cell cycle progression at various phases of the cell cycle (cyclins D3 and G2, MCM2 and MCM5, PLK1 and SMAD4). Thus miR-34a tempers the proliferative and pro-survival effect of growth factor stimulation by interfering with growth factor signal transduction and downstream pathways required for cell division., Competing Interests: The authors have declared that no competing interests exist.

The endoplasmic reticulum (ER) is the main site of protein and lipid synthesis, membrane biogenesis, xenobiotic detoxification and cellular calcium storage, and perturbation of ER homeostasis leads to stress and the activation of the unfolded protein response. Chronic activation of ER stress has been shown to have an important role in the development of insulin resistance and diabetes in obesity. However, the mechanisms that lead to chronic ER stress in a metabolic context in general, and in obesity in particular, are not understood. Here we comparatively examined the proteomic and lipidomic landscape of hepatic ER purified from lean and obese mice to explore the mechanisms of chronic ER stress in obesity. We found suppression of protein but stimulation of lipid synthesis in the obese ER without significant alterations in chaperone content. Alterations in ER fatty acid and lipid composition result in the inhibition of sarco/endoplasmic reticulum calcium ATPase (SERCA) activity and ER stress. Correcting the obesity-induced alteration of ER phospholipid composition or hepatic Serca overexpression in vivo both reduced chronic ER stress and improved glucose homeostasis. Hence, we established that abnormal lipid and calcium metabolism are important contributors to hepatic ER stress in obesity.

Unlabelled: The first open source software suite for experimentalists and curators that (i) assists in the annotation and local management of experimental metadata from high-throughput studies employing one or a combination of omics and other technologies; (ii) empowers users to uptake community-defined checklists and ontologies; and (iii) facilitates submission to international public repositories., Availability and Implementation: Software, documentation, case studies and implementations at http://www.isa-tools.org.

Combinatorial interactions among transcription factors are critical to directing tissue-specific gene expression. To build a global atlas of these combinations, we have screened for physical interactions among the majority of human and mouse DNA-binding transcription factors (TFs). The complete networks contain 762 human and 877 mouse interactions. Analysis of the networks reveals that highly connected TFs are broadly expressed across tissues, and that roughly half of the measured interactions are conserved between mouse and human. The data highlight the importance of TF combinations for determining cell fate, and they lead to the identification of a SMAD3/FLI1 complex expressed during development of immunity. The availability of large TF combinatorial networks in both human and mouse will provide many opportunities to study gene regulation, tissue differentiation, and mammalian evolution., ((c) 2010 Elsevier Inc. All rights reserved.)

miR-24, upregulated during terminal differentiation of multiple lineages, inhibits cell-cycle progression. Antagonizing miR-24 restores postmitotic cell proliferation and enhances fibroblast proliferation, whereas overexpressing miR-24 increases the G1 compartment. The 248 mRNAs downregulated upon miR-24 overexpression are highly enriched for DNA repair and cell-cycle regulatory genes that form a direct interaction network with prominent nodes at genes that enhance (MYC, E2F2, CCNB1, and CDC2) or inhibit (p27Kip1 and VHL) cell-cycle progression. miR-24 directly regulates MYC and E2F2 and some genes that they transactivate. Enhanced proliferation from antagonizing miR-24 is abrogated by knocking down E2F2, but not MYC, and cell proliferation, inhibited by miR-24 overexpression, is rescued by miR-24-insensitive E2F2. Therefore, E2F2 is a critical miR-24 target. The E2F2 3'UTR lacks a predicted miR-24 recognition element. In fact, miR-24 regulates expression of E2F2, MYC, AURKB, CCNA2, CDC2, CDK4, and FEN1 by recognizing seedless but highly complementary sequences.

Using deep sequencing (deepCAGE), the FANTOM4 study measured the genome-wide dynamics of transcription-start-site usage in the human monocytic cell line THP-1 throughout a time course of growth arrest and differentiation. Modeling the expression dynamics in terms of predicted cis-regulatory sites, we identified the key transcription regulators, their time-dependent activities and target genes. Systematic siRNA knockdown of 52 transcription factors confirmed the roles of individual factors in the regulatory network. Our results indicate that cellular states are constrained by complex networks involving both positive and negative regulatory interactions among substantial numbers of transcription factors and that no single transcription factor is both necessary and sufficient to drive the differentiation process.

The Alternative Splicing and Transcript Diversity database (ASTD) gives access to a vast collection of alternative transcripts that integrate transcription initiation, polyadenylation and splicing variant data. Alternative transcripts are derived from the mapping of transcribed sequences to the complete human, mouse and rat genomes using an extension of the computational pipeline developed for the ASD (Alternative Splicing Database) and ATD (Alternative Transcript Diversity) databases, which are now superseded by ASTD. For the human genome, ASTD identifies splicing variants, transcription initiation variants and polyadenylation variants in 68%, 68% and 62% of the gene set, respectively, consistent with current estimates for transcription variation. Users can access ASTD through a variety of browsing and query tools, including expression state-based queries for the identification of tissue-specific isoforms. Participating laboratories have experimentally validated a subset of ASTD-predicted alternative splice forms and alternative polyadenylation forms that were not previously reported. The ASTD database can be accessed at http://www.ebi.ac.uk/astd.

Cancer/Testis (CT) genes, normally expressed in germ line cells but also activated in a wide range of cancer types, often encode antigens that are immunogenic in cancer patients, and present potential for use as biomarkers and targets for immunotherapy. Using multiple in silico gene expression analysis technologies, including twice the number of expressed sequence tags used in previous studies, we have performed a comprehensive genome-wide survey of expression for a set of 153 previously described CT genes in normal and cancer expression libraries. We find that although they are generally highly expressed in testis, these genes exhibit heterogeneous gene expression profiles, allowing their classification into testis-restricted (39), testis/brain-restricted (14), and a testis-selective (85) group of genes that show additional expression in somatic tissues. The chromosomal distribution of these genes confirmed the previously observed dominance of X chromosome location, with CT-X genes being significantly more testis-restricted than non-X CT. Applying this core classification in a genome-wide survey we identified >30 CT candidate genes; 3 of them, PEPP-2, OTOA, and AKAP4, were confirmed as testis-restricted or testis-selective using RT-PCR, with variable expression frequencies observed in a panel of cancer cell lines. Our classification provides an objective ranking for potential CT genes, which is useful in guiding further identification and characterization of these potentially important diagnostic and therapeutic targets.

Unlabelled: The wcd system is an open source tool for clustering expressed sequence tags (EST) and other DNA and RNA sequences. wcd allows efficient all-versus-all comparison of ESTs using either the d(2) distance function or edit distance, improving existing implementations of d(2). It supports merging, refinement and reclustering of clusters. It is 'drop in' compatible with the StackPack clustering package. wcd supports parallelization under both shared memory and cluster architectures. It is distributed with an EMBOSS wrapper allowing wcd to be installed as part of an EMBOSS installation (and so provided by a web server)., Availability: wcd is distributed under a GPL licence and is available from http://code.google.com/p/wcdest., Supplementary Information: Additional experimental results. The wcd manual, a companion paper describing underlying algorithms, and all datasets used for experimentation can also be found at www.bioinf.wits.ac.za/~scott/wcdsupp.html.

One of the most important genetic factors known to affect the rate of disease progression in HIV-infected individuals is the genotype at the Class I Human Leukocyte Antigen (HLA) locus, which determines the HIV peptides targeted by cytotoxic T-lymphocytes (CTLs). Individuals with HLA-B*57 or B*5801 alleles, for example, target functionally important parts of the Gag protein. Mutants that escape these CTL responses may have lower fitness than the wild-type and can be associated with slower disease progression. Transmission of the escape variant to individuals without these HLA alleles is associated with rapid reversion to wild-type. However, the question of whether infection with an escape mutant offers an advantage to newly infected hosts has not been addressed. Here we investigate the relationship between the genotypes of transmitted viruses and prognostic markers of disease progression and show that infection with HLA-B*57/B*5801 escape mutants is associated with lower viral load and higher CD4+ counts.

Background: Fetal alcohol syndrome (FAS) is a serious global health problem and is observed at high frequencies in certain South African communities. Although in utero alcohol exposure is the primary trigger, there is evidence for genetic- and other susceptibility factors in FAS development. No genome-wide association or linkage studies have been performed for FAS, making computational selection and -prioritization of candidate disease genes an attractive approach., Results: 10174 Candidate genes were initially selected from the whole genome using a previously described method, which selects candidate genes according to their expression in disease-affected tissues. Hereafter candidates were prioritized for experimental investigation by investigating criteria pertinent to FAS and binary filtering. 29 Criteria were assessed by mining various database sources to populate criteria-specific gene lists. Candidate genes were then prioritized for experimental investigation using a binary system that assessed the criteria gene lists against the candidate list, and candidate genes were scored accordingly. A group of 87 genes was prioritized as candidates and for future experimental validation. The validity of the binary prioritization method was assessed by investigating the protein-protein interactions, functional enrichment and common promoter element binding sites of the top-ranked genes., Conclusion: This analysis highlighted a list of strong candidate genes from the TGF-beta, MAPK and Hedgehog signalling pathways, which are all integral to fetal development and potential targets for alcohol's teratogenic effect. We conclude that this novel bioinformatics approach effectively prioritizes credible candidate genes for further experimental analysis.

Activation of macrophages and subsequent "killing" effector functions against infectious pathogens are essential for the establishment of protective immunity. NF-IL6 is a transcription factor downstream of IFN-gamma and TNF in the macrophage activation pathway required for bacterial killing. Comparison of microarray expression profiles of Listeria monocytogenes (LM)-infected macrophages from WT and NF-IL6-deficient mice enabled us to identify candidate genes downstream of NF-IL6 involved in the unknown pathways of LM killing independent of reactive oxygen intermediates and reactive nitrogen intermediates. One differentially expressed gene, PKCdelta, had higher mRNA levels in the LM-infected NF-IL6-deficient macrophages as compared with WT. To define the role of PKCdelta during listeriosis, we infected PKCdelta-deficient mice with LM. PKCdelta-deficient mice were highly susceptible to LM infection with increased bacterial burden and enhanced histopathology despite enhanced NF-IL6 mRNA expression. Subsequent studies in PKCdelta-deficient macrophages demonstrated that, despite elevated levels of proinflammatory cytokines and NO production, increased escape of LM from the phagosome into the cytoplasm and uncontrolled bacterial growth occurred. Taken together these data identified PKCdelta as a critical factor for confinement of LM within macrophage phagosomes.

Background: Cancer/testis (CT) genes are normally expressed only in germ cells, but can be activated in the cancer state. This unusual property, together with the finding that many CT proteins elicit an antigenic response in cancer patients, has established a role for this class of genes as targets in immunotherapy regimes. Many families of CT genes have been identified in the human genome, but their biological function for the most part remains unclear. While it has been shown that some CT genes are under diversifying selection, this question has not been addressed before for the class as a whole., Results: To shed more light on this interesting group of genes, we exploited the generation of a draft chimpanzee (Pan troglodytes) genomic sequence to examine CT genes in an organism that is closely related to human, and generated a high-quality, manually curated set of human:chimpanzee CT gene alignments. We find that the chimpanzee genome contains homologues to most of the human CT families, and that the genes are located on the same chromosome and at a similar copy number to those in human. Comparison of putative human:chimpanzee orthologues indicates that CT genes located on chromosome X are diverging faster and are undergoing stronger diversifying selection than those on the autosomes or than a set of control genes on either chromosome X or autosomes., Conclusion: Given their high level of diversifying selection, we suggest that CT genes are primarily responsible for the observed rapid evolution of protein-coding genes on the X chromosome.

Model organisms represent an important resource for understanding the fundamental aspects of mammalian biology. Mapping of biological phenomena between model organisms is complex and if it is to be meaningful, a simplified representation can be a powerful means for comparison. The Developmental eVOC ontologies presented here are simplified orthogonal ontologies describing the temporal and spatial distribution of developmental human and mouse anatomy. We demonstrate the ontologies by identifying genes showing a bias for developmental brain expression in human and mouse.

Genome-wide experimental methods to identify disease genes, such as linkage analysis and association studies, generate increasingly large candidate gene sets for which comprehensive empirical analysis is impractical. Computational methods employ data from a variety of sources to identify the most likely candidate disease genes from these gene sets. Here, we review seven independent computational disease gene prioritization methods, and then apply them in concert to the analysis of 9556 positional candidate genes for type 2 diabetes (T2D) and the related trait obesity. We generate and analyse a list of nine primary candidate genes for T2D genes and five for obesity. Two genes, LPL and BCKDHA, are common to these two sets. We also present a set of secondary candidates for T2D (94 genes) and for obesity (116 genes) with 58 genes in common to both diseases.

Using the two largest collections of Mus musculus and Homo sapiens transcription start sites (TSSs) determined based on CAGE tags, ditags, full-length cDNAs, and other transcript data, we describe the compositional landscape surrounding TSSs with the aim of gaining better insight into the properties of mammalian promoters. We classified TSSs into four types based on compositional properties of regions immediately surrounding them. These properties highlighted distinctive features in the extended core promoters that helped us delineate boundaries of the transcription initiation domain space for both species. The TSS types were analyzed for associations with initiating dinucleotides, CpG islands, TATA boxes, and an extensive collection of statistically significant cis-elements in mouse and human. We found that different TSS types show preferences for different sets of initiating dinucleotides and cis-elements. Through Gene Ontology and eVOC categories and tissue expression libraries we linked TSS characteristics to expression. Moreover, we show a link of TSS characteristics to very specific genomic organization in an example of immune-response-related genes (GO:0006955). Our results shed light on the global properties of the two transcriptomes not revealed before and therefore provide the framework for better understanding of the transcriptional mechanisms in the two species, as well as a framework for development of new and more efficient promoter- and gene-finding tools., Competing Interests: Competing interests. The authors have declared that no competing interests exist.

LIFEdb (http://www.LIFEdb.de) integrates data from large-scale functional genomics assays and manual cDNA annotation with bioinformatics gene expression and protein analysis. New features of LIFEdb include (i) an updated user interface with enhanced query capabilities, (ii) a configurable output table and the option to download search results in XML, (iii) the integration of data from cell-based screening assays addressing the influence of protein-overexpression on cell proliferation and (iv) the display of the relative expression ('Electronic Northern') of the genes under investigation using curated gene expression ontology information. LIFEdb enables researchers to systematically select and characterize genes and proteins of interest, and presents data and information via its user-friendly web-based interface.

Background: The continuous flow of EST data remains one of the richest sources for discoveries in modern biology. The first step in EST data mining is usually associated with EST clustering, the process of grouping of original fragments according to their annotation, similarity to known genomic DNA or each other. Clustered EST data, accumulated in databases such as UniGene, STACK and TIGR Gene Indices have proven to be crucial in research areas from gene discovery to regulation of gene expression., Results: We have developed a new nucleotide sequence matching algorithm and its implementation for clustering EST sequences. The program is based on the original CLU match detection algorithm, which has improved performance over the widely used d2&#95;cluster. The CLU algorithm automatically ignores low-complexity regions like poly-tracts and short tandem repeats., Conclusion: CLU represents a new generation of EST clustering algorithm with improved performance over current approaches. An early implementation can be applied in small and medium-size projects. The CLU program is available on an open source basis free of charge. It can be downloaded from http://compbio.pbrc.edu/pti.

Given the medical and agricultural significance of Glossina, knowledge of the genomic aspects of the vector and vector-pathogen interactions are a high priority. In preparation for a full genome sequence initiative, an extensive set of expressed sequence tags (ESTs) has been generated from tissue-specific normalized libraries. In addition, bacterial artificial chromosome (BAC) libraries are being constructed, and information on the genome structure and size from different species has been obtained. An international consortium is now in place to further efforts to lead to a full genome project.

The Human Anatomic Gene Expression Library (H-ANGEL) is a resource for information concerning the anatomical distribution and expression of human gene transcripts. The tool contains protein expression data from multiple platforms that has been associated with both manually annotated full-length cDNAs from H-InvDB and RefSeq sequences. Of the H-Inv predicted genes, 18 897 have associated expression data generated by at least one platform. H-ANGEL utilizes categorized mRNA expression data from both publicly available and proprietary sources. It incorporates data generated by three types of methods from seven different platforms. The data are provided to the user in the form of a web-based viewer with numerous query options. H-ANGEL is updated with each new release of cDNA and genome sequence build. In future editions, we will incorporate the capability for expression data updates from existing and new platforms. H-ANGEL is accessible at http://www.jbirc.aist.go.jp/hinv/h-angel/.

The human genome sequence defines our inherent biological potential; the realization of the biology encoded therein requires knowledge of the function of each gene. Currently, our knowledge in this area is still limited. Several lines of investigation have been used to elucidate the structure and function of the genes in the human genome. Even so, gene prediction remains a difficult task, as the varieties of transcripts of a gene may vary to a great extent. We thus performed an exhaustive integrative characterization of 41,118 full-length cDNAs that capture the gene transcripts as complete functional cassettes, providing an unequivocal report of structural and functional diversity at the gene level. Our international collaboration has validated 21,037 human gene candidates by analysis of high-quality full-length cDNA clones through curation using unified criteria. This led to the identification of 5,155 new gene candidates. It also manifested the most reliable way to control the quality of the cDNA clones. We have developed a human gene database, called the H-Invitational Database (H-InvDB; http://www.h-invitational.jp/). It provides the following: integrative annotation of human genes, description of gene structures, details of novel alternative splicing isoforms, non-protein-coding RNAs, functional domains, subcellular localizations, metabolic pathways, predictions of protein three-dimensional structure, mapping of known single nucleotide polymorphisms (SNPs), identification of polymorphic microsatellite repeats within human genes, and comparative results with mouse full-length cDNAs. The H-InvDB analysis has shown that up to 4% of the human genome sequence (National Center for Biotechnology Information build 34 assembly) may contain misassembled or missing regions. We found that 6.5% of the human gene candidates (1,377 loci) did not have a good protein-coding open reading frame, of which 296 loci are strong candidates for non-protein-coding RNA genes. In addition, among 72,027 uniquely mapped SNPs and insertions/deletions localized within human genes, 13,215 nonsynonymous SNPs, 315 nonsense SNPs, and 452 indels occurred in coding regions. Together with 25 polymorphic microsatellite repeats present in coding regions, they may alter protein structure, causing phenotypic effects or resulting in disease. The H-InvDB platform represents a substantial contribution to resources needed for the exploration of human biology and pathology., Competing Interests: The authors have declared that no conflicts of interest exist.

Understanding and harnessing cellular potency are fundamental in biology and are also critical to the future therapeutic use of stem cells. Transcriptome analysis of these pluripotent cells is a first step towards such goals. Starting with sources that include oocytes, blastocysts, and embryonic and adult stem cells, we obtained 249,200 high-quality EST sequences and clustered them with public sequences to produce an index of approximately 30,000 total mouse genes that includes 977 previously unidentified genes. Analysis of gene expression levels by EST frequency identifies genes that characterize preimplantation embryos, embryonic stem cells, and adult stem cells, thus providing potential markers as well as clues to the functional features of these cells. Principal component analysis identified a set of 88 genes whose average expression levels decrease from oocytes to blastocysts, stem cells, postimplantation embryos, and finally to newborn tissues. This can be a first step towards a possible definition of a molecular scale of cellular potency. The sequences and cDNA clones recovered in this work provide a comprehensive resource for genes functioning in early mouse embryos and stem cells. The nonrestricted community access to the resource can accelerate a wide range of research, particularly in reproductive and regenerative medicine., Competing Interests: The authors have declared that no conflicts of interest exist.

Whereas genome sequencing defines the genetic potential of an organism, transcript sequencing defines the utilization of this potential and links the genome with most areas of biology. To exploit the information within the human genome in the fight against cancer, we have deposited some two million expressed sequence tags (ESTs) from human tumors and their corresponding normal tissues in the public databases. The data currently define approximately 23,500 genes, of which only approximately 1,250 are still represented only by ESTs. Examination of the EST coverage of known cancer-related (CR) genes reveals that <1% do not have corresponding ESTs, indicating that the representation of genes associated with commonly studied tumors is high. The careful recording of the origin of all ESTs we have produced has enabled detailed definition of where the genes they represent are expressed in the human body. More than 100,000 ESTs are available for seven tissues, indicating a surprising variability of gene usage that has led to the discovery of a significant number of genes with restricted expression, and that may thus be therapeutically useful. The ESTs also reveal novel nonsynonymous germline variants (although the one-pass nature of the data necessitates careful validation) and many alternatively spliced transcripts. Although widely exploited by the scientific community, vindicating our totally open source policy, the EST data generated still provide extensive information that remains to be systematically explored, and that may further facilitate progress toward both the understanding and treatment of human cancers.

To provide standardised description of gene expression and cross platform querying of databases, we have developed eVOC (http://www.sanbi.ac.za/evoc/), consisting of four orthogonal ontologies which describe Anatomical System, Cell Type, Pathology and Developmental Stage. We have annotated 47 microarray expression data sets and all publicly available human cDNA and SAGE tag libraries. eVOC has been integrated with the public resource EnsMart, which provides linking of transcripts and libraries with expression terms and the human genome sequence (http://www.ensembl.org/Homo&#95;sapiens/martview).

Expression data contribute significantly to the biological value of the sequenced human genome, providing extensive information about gene structure and the pattern of gene expression. ESTs, together with SAGE libraries and microarray experiment information, provide a broad and rich view of the transcriptome. However, it is difficult to perform large-scale expression mining of the data generated by these diverse experimental approaches. Not only is the data stored in disparate locations, but there is frequent ambiguity in the meaning of terms used to describe the source of the material used in the experiment. Untangling semantic differences between the data provided by different resources is therefore largely reliant on the domain knowledge of a human expert. We present here eVOC, a system which associates labelled target cDNAs for microarray experiments, or cDNA libraries and their associated transcripts with controlled terms in a set of hierarchical vocabularies. eVOC consists of four orthogonal controlled vocabularies suitable for describing the domains of human gene expression data including Anatomical System, Cell Type, Pathology and Developmental Stage. We have curated and annotated 7016 cDNA libraries represented in dbEST, as well as 104 SAGE libraries,with expression information,and provide this as an integrated, public resource that allows the linking of transcripts and libraries with expression terms. Both the vocabularies and the vocabulary-annotated libraries can be retrieved from http://www.sanbi.ac.za/evoc/. Several groups are involved in developing this resource with the aim of unifying transcript expression information.

Improved techniques for defining disease-gene location and evaluating the biological candidacy of regional transcripts will hasten disease-gene discovery.

A set of 7407 cDNA clones (NIA mouse 7.4K) was assembled from >20 cDNA libraries constructed mainly from early mouse embryos, including several stem cell libraries. The clone set was assembled from embryonic and newborn organ libraries consisting of ~120,000 cDNA clones, which were initially re-arrayed into a set of ~11,000 unique cDNA clones. A set of tubes was constructed from the racks in this set to prevent contamination and potential mishandling errors in all further re-arrays. Sequences from this set (11K) were analyzed further for quality and clone identity, and high-quality clones with verified identity were re-arrayed into the final set (7.4K). The set is freely available, and a corresponding database was built to provide comprehensive annotation for those clones with known identity or homology, and has been made available through an extensive Web site that includes many link-outs to external databases and analysis servers.

In an effort to detect factors which may be under positive selection, a survey for such genes in two pathogenic strains of Helicobacter pylori (J99 and 26695) was performed. Based on an analysis of synonymous and nonsynonymous substitutions, we identified 19 candidate genes under positive selection. A search for homologues with known crystallographic structures revealed Escherichia coli carbomoyl phosphate synthetase as a homologue of H. pylori carbamoyl phosphate synthetase. Carbamoyl phosphate synthetase as isolated from E. coli is a heterodimeric enzyme that possesses two different but coupled functionalities and is involved in the first committed step in the separate biosynthetic pathways for arginine and pyrimidine nucleotides. In this study, we provide evidence indicating that one of these functionalities appears to be under selective pressure. Reports from previously published site-directed mutagenesis studies point to a decoupling of amidotransferase and synthetase activities. Implications of these findings for a metabolic enzyme under positive selection are discussed in terms of the mechanisms of H. pylori pathogenesis.