Genome-wide transcriptome mapping analysis identifies organ-specific gene expression patterns along human chromosomes

Identification of a secretory protein c19orf10 activated in hepatocellular carcinoma

The identification of genes involved in tumor growth is crucial for the development of inventive anticancer treatments. Here, we have cloned a 17-kDa secretory protein encoded by c19orf10 from hepatocellular carcinoma (HCC) serial analysis of gene expression libraries. Gene expression analysis indicated that c19orf10 was overexpressed in approximately two-thirds of HCC tissues compared to the adjacent noncancerous liver tissues, and its expression was significantly positively correlated with that of alpha-fetoprotein (AFP). Overexpression of c19orf10 enhanced cell proliferation of AFP-negative HLE cells, whereas knockdown of c19orf10 inhibited cell proliferation of AFP-positive Hep3B and HuH7 cells along with G1 cell cycle arrest. Supplementation of recombinant c19orf10 protein in culture media enhanced cell proliferation in HLE cells, and this effect was abolished by the addition of antibodies developed against c19orf10. Intriguingly, c19orf10 could regulate cell proliferation through the activation of Akt/mitogen-activated protein kinase pathways. Taken together, these data suggest that c19orf10 might be one of the growth factors and potential molecular targets activated in HCC.

TRAM (Transcriptome Mapper): database-driven creation and analysis of transcriptome maps from multiple sources

Background

Several tools have been developed to perform global gene expression profile data analysis, to search for specific chromosomal regions whose features meet defined criteria as well as to study neighbouring gene expression. However, most of these tools are tailored for a specific use in a particular context (e.g. they are species-specific, or limited to a particular data format) and they typically accept only gene lists as input.

Results

TRAM (Transcriptome Mapper) is a new general tool that allows the simple generation and analysis of quantitative transcriptome maps, starting from any source listing gene expression values for a given gene set (e.g. expression microarrays), implemented as a relational database. It includes a parser able to assign univocal and updated gene symbols to gene identifiers from different data sources. Moreover, TRAM is able to perform intra-sample and inter-sample data normalization, including an original variant of quantile normalization (scaled quantile), useful to normalize data from platforms with highly different numbers of investigated genes. When in 'Map' mode, the software generates a quantitative representation of the transcriptome of a sample (or of a pool of samples) and identifies if segments of defined lengths are over/under-expressed compared to the desired threshold. When in 'Cluster' mode, the software searches for a set of over/under-expressed consecutive genes. Statistical significance for all results is calculated with respect to genes localized on the same chromosome or to all genome genes. Transcriptome maps, showing differential expression between two sample groups, relative to two different biological conditions, may be easily generated. We present the results of a biological model test, based on a meta-analysis comparison between a sample pool of human CD34+ hematopoietic progenitor cells and a sample pool of megakaryocytic cells. Biologically relevant chromosomal segments and gene clusters with differential expression during the differentiation toward megakaryocyte were identified.

Conclusions

TRAM is designed to create, and statistically analyze, quantitative transcriptome maps, based on gene expression data from multiple sources. The release includes FileMaker Pro database management runtime application and it is freely available at http://apollo11.isto.unibo.it/software/, along with preconfigured implementations for mapping of human, mouse and zebrafish transcriptomes.

Coherent expression chromosome cluster analysis reveals differential regulatory functions of amino-terminal and distal parathyroid hormone-related protein domains in prostate carcinoma

Parathyroid hormone-related protein (PTHrP) has a number of cancer-related actions. While best known for causing hypercalcemia of malignancy, it also has effects on cancer cell growth, apoptosis, and angiogenesis. Studying the actions of PTHrP in human cancer is complicated because there are three isoforms and many derived peptides. Several peptides are biologically active at known or presumed cell surface receptors; in addition, the PTHrP-derived molecules can exert effects at the cell nucleus. To address this complexity, we studied gene expression in a DU 145 prostate cancer cell line that was stably transfected with control vector, PTHrP 1-173 and PTHrP 33-173. With this model, regulatory effects of the amino-terminal portion of PTHrP would result only from transduction with the full-length molecule, while effects pertaining to distal sequences would be evident with either construct. Analysis of the expression profiles by microarrays demonstrated nonoverlapping groups of differentially expressed genes. Amino-terminal PTHrP affected groups of genes involved in apoptosis, prostaglandin and sex steroid metabolism, cell-matrix interactions, and cell differentiation, while PTHrP 33-173 caused substantial increases in MHC class I antigen expression. This work demonstrates the distinct biological actions of the amino-terminus compared to distal mid-molecule or carboxy-terminal sequences of PTHrP in prostate carcinoma cells and provides targets for further study of the malignant process.

Individualized treatment of chronic hepatitis C with pegylated interferon and ribavirin

Chronic infection with hepatitis C virus (HCV) is a major public health problem, with perhaps 180 million people infected worldwide. A significant proportion of these will eventually develop clinical complications, such as cirrhosis, liver decompensation and hepatocellular carcinoma. Sustained virological response (SVR) to antiviral therapy is associated with improvement in liver histology and survival free of liver-related complications. Great effort has been made to improve SVR rate by adapting the duration of therapy according to HCV genotype and to on-treatment response. Rapid virological response (RVR, undetectable HCV RNA at week 4) usually has a high positive predictive value for achieving SVR and early virological response (EVR, ≥ 2 log reduction or undetectable HCV RNA at week 12) exhibits a high negative predictive value for non-response. Individualized approach can improve cost-effectiveness of HCV antiviral therapy by reducing side effects and the costs of therapy associated with unnecessary exposure to treatment and through extending therapy for those with unfavorable features. This article summarizes recent data on strategies of individualized treatment in naïve patients with mono-infection by the different HCV genotypes. The management of common side effects, the impact of HCV infection on health-related quality of life and the potential applications of host genomics in HCV therapy are also briefly discussed.

dUTP pyrophosphatase expression correlates with a poor prognosis in hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is a malignancy with a poor prognosis, partly owing to the lack of biomarkers that support its classification in line with its malignant nature. To discover a novel molecular marker that is related to the efficacy of treatment for HCC and its biological nature, we performed serial analysis of gene expression (SAGE) in HCC, normal liver and cirrhotic liver tissues.

METHODS

Gene expression profiles of HCC tissues and non-cancerous liver tissues were obtained by SAGE. Suppression of the target gene by RNA interference was used to evaluate its role in HCC in vitro. The relation of the identified marker and prognosis was statistically examined in surgically resected HCC patients.

RESULTS

We identified significant overexpression of DUT, which encodes dUTP pyrophosphatase (dUTPase), in HCC tissue, and this was confirmed in about two-thirds of the HCC samples by reverse-transcription polymerase chain reaction (n=20). Suppression of dUTPase expression using short interfering RNAs inhibited cell proliferation and sensitized HuH7 cells to 5-fluorouracil treatment. Nuclear dUTPase expression was observed in 36.6% of surgically resected HCC samples (n=82) evaluated by immunohistochemistry, and its expression was significantly correlated with the histological grades (P=0.0099). Notably, nuclear dUTPase expression correlated with a poor prognosis with statistical significance (HR, 2.47; 95% CI, 1.08-5.66; P=0.032).

CONCLUSION

Taken together, these results suggest that nuclear dUTPase may be a good biomarker for predicting prognosis in HCC patients after surgical resection. Development of novel dUTPase inhibitors may facilitate the eradication of HCC.

QTL global meta-analysis: are trait determining genes clustered?

Background

A key open question in biology is if genes are physically clustered with respect to their known functions or phenotypic effects. This is of particular interest for Quantitative Trait Loci (QTL) where a QTL region could contain a number of genes that contribute to the trait being measured.

Results

We observed a significant increase in gene density within QTL regions compared to non-QTL regions and/or the entire bovine genome. By grouping QTL from the Bovine QTL Viewer database into 8 categories of non-redundant regions, we have been able to analyze gene density and gene function distribution, based on Gene Ontology (GO) with relation to their location within QTL regions, outside of QTL regions and across the entire bovine genome. We identified a number of GO terms that were significantly over represented within particular QTL categories. Furthermore, select GO terms expected to be associated with the QTL category based on common biological knowledge have also proved to be significantly over represented in QTL regions.

Conclusion

Our analysis provides evidence of over represented GO terms in QTL regions. This increased GO term density indicates possible clustering of gene functions within QTL regions of the bovine genome. Genes with similar functions may be grouped in specific locales and could be contributing to QTL traits. Moreover, we have identified over-represented GO terminology that from a biological standpoint, makes sense with respect to QTL category type.

Contributions of extracellular matrix signaling and tissue architecture to nuclear mechanisms and spatial organization of gene expression control

Post-translational modification of histones, ATP-dependent chromatin remodeling, and DNA methylation are interconnected nuclear mechanisms that ultimately lead to the changes in chromatin structure necessary to carry out epigenetic gene expression control. Tissue differentiation is characterized by a specific gene expression profile in association with the acquisition of a defined tissue architecture and function. Elements critical for tissue differentiation, like extracellular stimuli, adhesion and cell shape properties, and transcription factors all contribute to the modulation of gene expression and thus, are likely to impinge on the nuclear mechanisms of epigenetic gene expression control. In this review, we analyze how these elements modify chromatin structure in a hierarchical manner by acting on the nuclear machinery. We discuss how mechanotransduction via the structural continuum of the cell and biochemical signaling to the cell nucleus integrate to provide a comprehensive control of gene expression. The role of nuclear organization in this control is highlighted, with a presentation of differentiation-induced nuclear structure and the concept of nuclear organization as a modulator of the response to incoming signals.

Chromatin domains in higher eukaryotes: insights from genome-wide mapping studies

In genomes of higher eukaryotes, adjacent genes often show coordinated regulation of their expression. Compartmentalization of multiple neighboring genes into a shared chromatin environment can facilitate this coordinated expression. New mapping techniques have begun to reveal that such multigene chromatin domains are a common feature of fly and mammalian genomes. Many different types of chromatin domains have been identified based on the genomic binding patterns of various proteins and histone modifications. In addition, maps of genome-nuclear lamina associations and of looping interactions between loci provide the first systematic views of the three-dimensional folding of interphase chromosomes. These genome-wide datasets uncover new architectural principles of eukaryotic genomes and indicate that multigene chromatin domains are prevalent and important regulatory units.

[Gene expression profiling in drug addicted brain]

Drug addiction, a chronic brain disease caused by interaction of in vitro drug toxification and in vivo gene susceptibility, has been widely studied but its underlining mechanism is so far been elucidated. A major goal in this field is to identify drug-induced molecular changes and their effects on brain function. By the advance of high throughput technologies in genomics and transcriptomics, the whole gene expression profile in addicted brain could be obtained and proved to be a very powerful tool to unclose the molecular mechanism underlying the addiction biology context. Here, we summarized the progress of serial analysis of gene expression (SAGE) and microarray, as well as their application in drug addiction.

CREB binding and activity in brain: regional specificity and induction by electroconvulsive seizure

BACKGROUND

The transcription factor cyclic adenosine monophosphate response element binding protein (CREB) orchestrates diverse neurobiological processes including cell differentiation, survival, and plasticity. Alterations in CREB-mediated transcription have been implicated in numerous central nervous system (CNS) disorders including depression, anxiety, addiction, and cognitive decline. However, it remains unclear how CREB contributes to normal and aberrant CNS function, as the identity of CREB-regulated genes in brain and the regional and temporal dynamics of CREB function remain largely undetermined.

METHODS

We combined microarray and chromatin immunoprecipitation technology to analyze CREB-DNA interactions in brain. We compared the occupancy and activity of CREB at gene promoters in rat frontal cortex, hippocampus, and striatum before and after a rodent model of electroconvulsive therapy.

RESULTS

Our analysis identified >860 CREB binding sites in rat brain. We identified multiple genomic loci enriched with CREB binding sites and find that CREB-occupied transcripts interact extensively to promote cell proliferation, plasticity, and resiliency. We discovered regional differences in CREB occupancy and activity that explain, in part, the diverse biological and behavioral outputs of CREB activity in frontal cortex, hippocampus, and striatum. Electroconvulsive seizure rapidly increased CREB occupancy and/or phosphorylation at select promoters, demonstrating that both events contribute to the temporal regulation of the CREB transcriptome.

CONCLUSIONS

Our data provide a mechanistic basis for CREB's ability to integrate regional and temporal cues to orchestrate state-specific patterns of transcription in the brain, indicate that CREB is an important mediator of the biological responses to electroconvulsive seizure, and provide global mechanistic insights into CREB's role in psychiatric and cognitive function.

Genomic expression during human myelopoiesis

Background

Human myelopoiesis is an exciting biological model for cellular differentiation since it represents a plastic process where multipotent stem cells gradually limit their differentiation potential, generating different precursor cells which finally evolve into distinct terminally differentiated cells. This study aimed at investigating the genomic expression during myeloid differentiation through a computational approach that integrates gene expression profiles with functional information and genome organization.

Results

Gene expression data from 24 experiments for 8 different cell types of the human myelopoietic lineage were used to generate an integrated myelopoiesis dataset of 9,425 genes, each reliably associated to a unique genomic position and chromosomal coordinate. Lists of genes constitutively expressed or silent during myelopoiesis and of genes differentially expressed in commitment phase of myelopoiesis were first identified using a classical data analysis procedure. Then, the genomic distribution of myelopoiesis genes was investigated integrating transcriptional and functional characteristics of genes. This approach allowed identifying specific chromosomal regions significantly highly or weakly expressed, and clusters of differentially expressed genes and of transcripts related to specific functional modules.

Conclusion

The analysis of genomic expression during human myelopoiesis using an integrative computational approach allowed discovering important relationships between genomic position, biological function and expression patterns and highlighting chromatin domains, including genes with coordinated expression and lineage-specific functions.

Computational and biological inference of gene regulatory networks of the LINE-1 retrotransposon

Computational approaches were used to define structural and functional determinants of a putative genetic regulatory network of murine LINE-1 (long interspersed nuclear element-1), an active mammalian retrotransposon that uses RNA intermediates to populate new sites throughout the genome. Polymerase (RNA) II polypeptide E AI845735 and mouse DNA homologous to Drosophila per fragment M12039 were identified as primary attractors. siRNA knockdown of the aryl hydrocarbon receptor NM_013464 modulated gene expression within the network, including LINE-1, Sgpl1, Sdcbp, and Mgst1. Genes within the network did not exhibit physical proximity and instead were dispersed throughout the genome. The potential impact of individual members of the network on the global dynamical behavior of LINE-1 was examined from a theoretical and empirical framework.

The hepatic transcriptome in human liver disease

The transcriptome is the mRNA transcript pool in a cell, organ or tissue with the liver transcriptome being amongst the most complex of any organ. Functional genomics methodologies are now being widely utilized to study transcriptomes including the hepatic transcriptome. This review outlines commonly used methods of transcriptome analysis, especially gene array analysis, focusing on publications utilizing these methods to understand human liver disease. Additionally, we have outlined the relationship between transcript and protein expressions as well as summarizing what is known about the variability of the transcriptome in non-diseased liver tissue. The approaches covered include gene array analysis, serial analysis of gene expression, subtractive hybridization and differential display. The discussion focuses on primate whole organ studies and in-vitro cell culture systems utilized. It is now clear that there are a vast number research opportunities for transcriptome analysis of human liver disease as we attempt to better understand both non-diseased and disease hepatic mRNA expression. We conclude that hepatic transcriptome analysis has already made significant contributions to the understanding of human liver pathobiology.

REEF: searching REgionally Enriched Features in genomes

Background

In Eukaryotic genomes, different features including genes are not uniformly distributed. The integration of annotation information and genomic position of functional DNA elements in the Eukaryotic genomes opened the way to test novel hypotheses of higher order genome organization and regulation of expression.

Results

REEF is a new tool, aimed at identifying genomic regions enriched in specific features, such as a class or group of genes homogeneous for expression and/or functional characteristics. The method for the calculation of local feature enrichment uses test statistic based on the Hypergeometric Distribution applied genome-wide by using a sliding window approach and adopting the False Discovery Rate for controlling multiplicity. REEF software, source code and documentation are freely available at .

Conclusion

REEF can aid to shed light on the role of organization of specific genomic regions in the determination of their functional role.

Active chromatin hub of the mouse alpha-globin locus forms in a transcription factory of clustered housekeeping genes

RNA polymerases can be shared by a particular group of genes in a transcription "factory" in nuclei, where transcription may be coordinated in concert with the distribution of coexpressed genes in higher-eukaryote genomes. Moreover, gene expression can be modulated by regulatory elements working over a long distance. Here, we compared the conformation of a 130-kb chromatin region containing the mouse alpha-globin cluster and their flanking housekeeping genes in 14.5-day-postcoitum fetal liver and brain cells. The analysis of chromatin conformation showed that the active alpha1 and alpha2 globin genes and upstream regulatory elements are in close spatial proximity, indicating that looping may function in the transcriptional regulation of the mouse alpha-globin cluster. In fetal liver cells, the active alpha1 and alpha2 genes, but not the inactive zeta gene, colocalize with neighboring housekeeping genes C16orf33, C16orf8, MPG, and C16orf35. This is in sharp contrast with the mouse alpha-globin genes in nonexpressing cells, which are separated from the congregated housekeeping genes. A comparison of RNA polymerase II (Pol II) occupancies showed that active alpha1 and alpha2 gene promoters have a much higher RNA Pol II enrichment in liver than in brain. The RNA Pol II occupancy at the zeta gene promoter, which is specifically repressed during development, is much lower than that at the alpha1 and alpha2 promoters. Thus, the mouse alpha-globin gene cluster may be regulated through moving in or out active globin gene promoters and regulatory elements of a preexisting transcription factory in the nucleus, which is maintained by the flanking clustered housekeeping genes, to activate or inactivate alpha-globin gene expression.

A transcriptome anatomy of human colorectal cancers

Background

Accumulating databases in human genome research have enabled integrated genome-wide study on complicated diseases such as cancers. A practical approach is to mine a global transcriptome profile of disease from public database. New concepts of these diseases might emerge by landscaping this profile.

Methods

In this study, we clustered human colorectal normal mucosa (N), inflammatory bowel disease (IBD), adenoma (A) and cancer (T) related expression sequence tags (EST) into UniGenes via an in-house GetUni software package and analyzed the transcriptome overview of these libraries by GOTree Machine (GOTM). Additionally, we downloaded UniGene based cDNA libraries of colon and analyzed them by Xprofiler to cross validate the efficiency of GetUni. Semi-quantitative RT-PCR was used to validate the expression of β-catenin and. 7 novel genes in colorectal cancers.

Results

The efficiency of GetUni was successfully validated by Xprofiler and RT-PCR. Genes in library N, IBD and A were all found in library T. A total of 14,879 genes were identified with 2,355 of them having at least 2 transcripts. Differences in gene enrichment among these libraries were statistically significant in 50 signal transduction pathways and Pfam protein domains by GOTM analysis P < 0.01 Hypergeometric Test). Genes in two metabolic pathways, ribosome and glycolysis, were more enriched in the expression profiles of A and IBD than in N and T. Seven transmembrane receptor superfamily genes were typically abundant in cancers.

Conclusion

Colorectal cancers are genetically heterogeneous. Transcription variants are common in them. Aberrations of ribosome and glycolysis pathway might be early indicators of precursor lesions in colon cancers. The electronic gene expression profile could be used to highlight the integral molecular events in colorectal cancers.

Structure and function of the human genome

The human genome project has had an impact on both biological research and its political organization; this review focuses primarily on the scientific novelty that has emerged from the project but also touches on its political dimensions. The project has generated both anticipated and novel information; in the later category are the description of the unusual distribution of genes, the prevalence of non-protein-coding genes, and the extraordinary evolutionary conservation of some regions of the genome. The applications of the sequence data are just starting to be felt in basic, rather than therapeutic, biomedical research and in the vibrant human origins and variation debates. The political impact of the project is in the unprecedented extent to which directed funding programs have emerged as drivers of basic research and the organization of the multidisciplinary groups that are needed to utilize the human DNA sequence.

Global analysis of IL-2 target genes: identification of chromosomal clusters of expressed genes

T lymphocytes play a central role in controlling adaptive immune responses. IL-2 critically regulates both T cell growth and death and is involved in maintaining peripheral tolerance, but the molecules involved in these and other IL-2 actions are only partially known. We now provide a comprehensive compendium of the genes expressed in T cells and of those regulated by IL-2 based on a combination of DNA microarrays and serial analysis of gene expression (SAGE). The newly identified IL-2 target genes include many genes previously linked to apoptosis in other cellular systems that may contribute to IL-2-dependent survival functions. We also studied the mRNA expression of known regulators of signaling pathways for their induction in response to IL-2 in order to identify potential novel positive and/or negative feedback regulators of IL-2 signaling. We show that IL-2 regulates only a limited number of these genes. These include suppressors of cytokine signaling (SOCS) 1, SOCS2, dual-specificity phosphatase (DUSP) 5, DUSP6 and non-receptor type phosphatase-7 (PTPN7). Additionally, we provide evidence that many genes expressed in T cells locate in chromosomal clusters, and that select IL-2-regulated genes are located in at least two clusters, one at 5q31, a known cytokine gene cluster, and the other at 6p21.3, a region that contains genes encoding the tumor necrosis factor (TNF) superfamily members TNF, LT-alpha and LT-beta.

A non-random walk through the genome

Genes showing particular expression patterns are not randomly distributed in the genome but are clustered into neighborhoods. This organization may be related to chromatin and the structure of the nucleus.

Recent publications on a wide range of eukaryotes indicate that genes showing particular expression patterns are not randomly distributed in the genome but are clustered into contiguous regions that we call neighborhoods. It seems probable that this organization is related to chromatin and the structure of the nucleus.