Study of cerebral gene expression densities using Voronoi analysis

As the available public cerebral gene expression image data increasingly grows, the demand for automated methods to analyze such large amount of data also increases. An important study that can be carried out on these data is related to the spatial relationship between gene expressions. Similar spatial density distribution of expression between genes may indicate they are functionally correlated, thus the identification of these similarities is useful in suggesting directions of investigation to discover gene interactions and their correlated functions. In this paper, we describe the use of a high-throughput methodology based on Voronoi diagrams to automatically analyze and search for possible local spatial density relationships between gene expression images. We tested this method using mouse brain section images from the Allen Mouse Brain Atlas public database. This methodology provided measurements able to characterize the similarity of the density distribution between gene expressions and allowed the visualization of the results through networks and Principal Component Analysis (PCA). These visualizations are useful to analyze the similarity level between gene expression patterns, as well as to compare connection patterns between region networks. Some genes were found to have the same type of function and to be near each other in the PCA visualizations. These results suggest cerebral density correlations between gene expressions that could be further explored. (C) 2011 Elsevier B.V. All rights reserved.

Bayesian model accounting for within-class biological variability in Serial Analysis of Gene Expression (SAGE)

Abstract Background An important challenge for transcript counting methods such as Serial Analysis of Gene Expression (SAGE), "Digital Northern" or Massively Parallel Signature Sequencing (MPSS), is to carry out statistical analyses that account for the within-class variability, i.e., variability due to the intrinsic biological differences among sampled individuals of the same class, and not only variability due to technical sampling error. Results We introduce a Bayesian model that accounts for the within-class variability by means of mixture distribution. We show that the previously available approaches of aggregation in pools ("pseudo-libraries") and the Beta-Binomial model, are particular cases of the mixture model. We illustrate our method with a brain tumor vs. normal comparison using SAGE data from public databases. We show examples of tags regarded as differentially expressed with high significance if the within-class variability is ignored, but clearly not so significant if one accounts for it. Conclusion Using available information about biological replicates, one can transform a list of candidate transcripts showing differential expression to a more reliable one. Our method is freely available, under GPL/GNU copyleft, through a user friendly web-based on-line tool or as R language scripts at supplemental web-site.

Analysis of ripening-related gene expression in papaya using an Arabidopsis-based microarray

Abstract Background Papaya (Carica papaya L.) is a commercially important crop that produces climacteric fruits with a soft and sweet pulp that contain a wide range of health promoting phytochemicals. Despite its importance, little is known about transcriptional modifications during papaya fruit ripening and their control. In this study we report the analysis of ripe papaya transcriptome by using a cross-species (XSpecies) microarray technique based on the phylogenetic proximity between papaya and Arabidopsis thaliana. Results Papaya transcriptome analyses resulted in the identification of 414 ripening-related genes with some having their expression validated by qPCR. The transcription profile was compared with that from ripening tomato and grape. There were many similarities between papaya and tomato especially with respect to the expression of genes encoding proteins involved in primary metabolism, regulation of transcription, biotic and abiotic stress and cell wall metabolism. XSpecies microarray data indicated that transcription factors (TFs) of the MADS-box, NAC and AP2/ERF gene families were involved in the control of papaya ripening and revealed that cell wall-related gene expression in papaya had similarities to the expression profiles seen in Arabidopsis during hypocotyl development. Conclusion The cross-species array experiment identified a ripening-related set of genes in papaya allowing the comparison of transcription control between papaya and other fruit bearing taxa during the ripening process.

Expression Analysis of the Theileria parva Subtelomere-Encoded Variable Secreted Protein Gene Family

Background The intracellular protozoan parasite Theileria parva transforms bovine lymphocytes inducing uncontrolled proliferation. Proteins released from the parasite are assumed to contribute to phenotypic changes of the host cell and parasite persistence. With 85 members, genes encoding subtelomeric variable secreted proteins (SVSPs) form the largest gene family in T. parva. The majority of SVSPs contain predicted signal peptides, suggesting secretion into the host cell cytoplasm. Methodology/Principal Findings We analysed SVSP expression in T. parva-transformed cell lines established in vitro by infection of T or B lymphocytes with cloned T. parva parasites. Microarray and quantitative real-time PCR analysis revealed mRNA expression for a wide range of SVSP genes. The pattern of mRNA expression was largely defined by the parasite genotype and not by host background or cell type, and found to be relatively stable in vitro over a period of two months. Interestingly, immunofluorescence analysis carried out on cell lines established from a cloned parasite showed that expression of a single SVSP encoded by TP03_0882 is limited to only a small percentage of parasites. Epitope-tagged TP03_0882 expressed in mammalian cells was found to translocate into the nucleus, a process that could be attributed to two different nuclear localisation signals. Conclusions Our analysis reveals a complex pattern of Theileria SVSP mRNA expression, which depends on the parasite genotype. Whereas in cell lines established from a cloned parasite transcripts can be found corresponding to a wide range of SVSP genes, only a minority of parasites appear to express a particular SVSP protein. The fact that a number of SVSPs contain functional nuclear localisation signals suggests that proteins released from the parasite could contribute to phenotypic changes of the host cell. This initial characterisation will facilitate future studies on the regulation of SVSP gene expression and the potential biological role of these enigmatic proteins.

RNA-Seq-based analysis of the physiologic cold shock-induced changes in Moraxella catarrhalis gene expression

BACKGROUND Moraxella catarrhalis, a major nasopharyngeal pathogen of the human respiratory tract, is exposed to rapid downshifts of environmental temperature when humans breathe cold air. The prevalence of pharyngeal colonization and respiratory tract infections caused by M. catarrhalis is greatest in winter. We investigated how M. catarrhalis uses the physiologic exposure to cold air to regulate pivotal survival systems that may contribute to M. catarrhalis virulence. RESULTS In this study we used the RNA-seq techniques to quantitatively catalogue the transcriptome of M. catarrhalis exposed to a 26 °C cold shock or to continuous growth at 37 °C. Validation of RNA-seq data using quantitative RT-PCR analysis demonstrated the RNA-seq results to be highly reliable. We observed that a 26 °C cold shock induces the expression of genes that in other bacteria have been related to virulence a strong induction was observed for genes involved in high affinity phosphate transport and iron acquisition, indicating that M. catarrhalis makes a better use of both phosphate and iron resources after exposure to cold shock. We detected the induction of genes involved in nitrogen metabolism, as well as several outer membrane proteins, including ompA, m35-like porin and multidrug efflux pump (acrAB) indicating that M. catarrhalis remodels its membrane components in response to downshift of temperature. Furthermore, we demonstrate that a 26 °C cold shock enhances the induction of genes encoding the type IV pili that are essential for natural transformation, and increases the genetic competence of M. catarrhalis, which may facilitate the rapid spread and acquisition of novel virulence-associated genes. CONCLUSION Cold shock at a physiologically relevant temperature of 26 °C induces in M. catarrhalis a complex of adaptive mechanisms that could convey novel pathogenic functions and may contribute to enhanced colonization and virulence.

Analysis of differential gene expression in nontumorigenic glioblastoma multiforme

Loss of chromosome 10 represents the most common cytogenetic abnormality in high grade gliomas (glioblastoma multiforme). To identify genes involved in the malignant progression of human gliomas, a subtractive hybridization was performed between a tumorigenic glioblastoma cell line (LG11) and a nontumorgenic hybrid cell (LG11.3) containing an introduced chromosome 10. LG11 mRNA was subtracted from LG11.3 cDNA to produce cDNA probes enriched for sequences whose expression differs quantitatively from the parental tumorigenic cells. Both known and novel sequences were identified as a result of the subtraction. Northern blot analysis was then used to confirm differential expression of several subtracted clones. One novel clone, clone 17, identified a 2.6 kb message that showed a consistent two to four fold increase in expression in the LG11.3 nontumorigenic cells. Clone 17 (340 bp) was used successfully to screen for a near full-length version, RIG (regulated in glioma), which was 2,569 bp in size. The RIG cDNA sequence showed homology to clone 17 and to an anonymous EST (IB666), but to no previously identified genes. This screening effort also identified several independent clones representing novel sequences, most of which failed to show increased expression in the nontumorigenic GBM cells. Tissue distribution studies of RIG indicated highest levels of expression in human brain with appreciably lower levels in heart and lung. In vitro transcription and translation experiments demonstrated the ability of RIG to direct the synthesis of a 13 kD protein product. However, open reading frame analysis revealed no identify with previously described motifs or any known proteins. Using a combination of somatic cell hybrid panels and in situ hybridization, the RIG gene was mapped to chromosome 11p14-11p15. Further study of RIG and related gene products may provide insight into the negative regulation of glial oncogenesis. ^

Molecular cloning, expression analysis and assignment of the porcine tumor necrosis factor superfamily member 10 gene (TNFSF10) to SSC13q34-->q36 by fluorescence in situ hybridization and radiation hybrid mapping

We have cloned the complete coding region of the porcine TNFSF10 gene. The porcine TNFSF10 cDNA has an ORF of 870 nucleotides and shares 85% identity with human TNFSF10, and 75% and 72% identity with rat and mouse Tnfsf10 coding sequences, respectively. The deduced porcine TNFSF10 protein consists of 289 amino acids with the calculated molecular mass of 33.5 kDa and a predicted pI of 8.15. The amino acid sequence similarities correspond to 86, 72 and 70% when compared with human, rat and mouse sequences, respectively. Northern blot analysis detected TNFSF10-specific transcripts (approximately 1.7 kb) in various organs of a 10-week-old pig, suggesting ubiquitous expression. Real-time RT-PCR studies of various organs from fetal (days 73 and 98) and postnatal stages (two weeks, eight months) demonstrated developmental and tissue-specific regulation of TNFSF10 mRNA abundance. The chromosomal location of the porcine TNFSF10 gene was determined by FISH of a specific BAC clone to metaphase chromosomes. This TNFSF10 BAC clone has been assigned to SSC13q34-->q36. Additionally, the localization of the TNFSF10 gene was verified by RH mapping on the porcine IMpRH panel.

A Toolbox for Quantitative Gene Expression in Varroa destructor : RNA Degradation in Field Samples and Systematic Analysis of Reference Gene Stability

Funding: This project has received funding from the European Union’s Seventh Framework Programme for research, technological development and demonstration under grant agreement no. 613960 (SMARTBEES) (http://www.smartbees-fp7.eu/) and Veterinary Medicines Directorate, Department for Environment Food & Rural Affairs (Project # VM0517) (https://www.gov.uk/government/organisations/veterinary-medicines-directorate). CHM was supported by a Biosciences Knowledge Transfer Network Biotechnology and Biological Sciences Research Council (KTN-BBSRC CASE) Studentship (BB/L502467/1) (http://www.bbsrc.ac.uk/). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Acknowledgments We gratefully acknowledge Mr Sebastian Bacz’s expert help and advice with beekeeping.

Dynamics of Gene Expression Revealed by Comparison of Serial Analysis of Gene Expression Transcript Profiles from Yeast Grown on Two Different Carbon SourcesD⃞

We describe a genome-wide characterization of mRNA transcript levels in yeast grown on the fatty acid oleate, determined using Serial Analysis of Gene Expression (SAGE). Comparison of this SAGE library with that reported for glucose grown cells revealed the dramatic adaptive response of yeast to a change in carbon source. A major fraction (>20%) of the 15,000 mRNA molecules in a yeast cell comprised differentially expressed transcripts, which were derived from only 2% of the total number of ∼6300 yeast genes. Most of the mRNAs that were differentially expressed code for enzymes or for other proteins participating in metabolism (e.g., metabolite transporters). In oleate-grown cells, this was exemplified by the huge increase of mRNAs encoding the peroxisomal β-oxidation enzymes required for degradation of fatty acids. The data provide evidence for the existence of redox shuttles across organellar membranes that involve peroxisomal, cytoplasmic, and mitochondrial enzymes. We also analyzed the mRNA profile of a mutant strain with deletions of the PIP2 and OAF1 genes, encoding transcription factors required for induction of genes encoding peroxisomal proteins. Induction of genes under the immediate control of these factors was abolished; other genes were up-regulated, indicating an adaptive response to the changed metabolism imposed by the genetic impairment. We describe a statistical method for analysis of data obtained by SAGE.

Global analysis of gene expression in pulmonary fibrosis reveals distinct programs regulating lung inflammation and fibrosis

The molecular mechanisms of pulmonary fibrosis are poorly understood. We have used oligonucleotide arrays to analyze the gene expression programs that underlie pulmonary fibrosis in response to bleomycin, a drug that causes lung inflammation and fibrosis, in two strains of susceptible mice (129 and C57BL/6). We then compared the gene expression patterns in these mice with 129 mice carrying a null mutation in the epithelial-restricted integrin β6 subunit (β6−/−), which develop inflammation but are protected from pulmonary fibrosis. Cluster analysis identified two distinct groups of genes involved in the inflammatory and fibrotic responses. Analysis of gene expression at multiple time points after bleomycin administration revealed sequential induction of subsets of genes that characterize each response. The availability of this comprehensive data set should accelerate the development of more effective strategies for intervention at the various stages in the development of fibrotic diseases of the lungs and other organs.

Generation of longer cDNA fragments from serial analysis of gene expression tags for gene identification

We have developed a technique called the generation of longer cDNA fragments from serial analysis of gene expression (SAGE) tags for gene identification (GLGI), to convert SAGE tags of 10 bases into their corresponding 3′ cDNA fragments covering hundred bases. A primer containing the 10-base SAGE tag is used as the sense primer, and a single base anchored oligo(dT) primer is used as an antisense primer in PCR, together with Pfu DNA polymerase. By using this approach, a cDNA fragment extending from the SAGE tag toward the 3′ end of the corresponding sequence can be generated. Application of the GLGI technique can solve two critical issues in applying the SAGE technique: one is that a longer fragment corresponding to a SAGE tag, which has no match in databases, can be generated for further studies; the other is that the specific fragment corresponding to a SAGE tag can be identified from multiple sequences that match the same SAGE tag. The development of the GLGI method provides several potential applications. First, it provides a strategy for even wider application of the SAGE technique for quantitative analysis of global gene expression. Second, a combined application of SAGE/GLGI can be used to complete the catalogue of the expressed genes in human and in other eukaryotic species. Third, it can be used to identify the 3′ cDNA sequence from any exon within a gene. It can also be used to confirm the reality of exons predicted by bioinformatic tools in genomic sequences. Fourth, a combined application of SAGE/GLGI can be applied to define the 3′ boundary of expressed genes in the genomic sequences in human and in other eukaryotic genomes.

Toward functional genomics in bacteria: Analysis of gene expression in Escherichia coli from a bacterial artificial chromosome library of Bacillus cereus

As the study of microbes moves into the era of functional genomics, there is an increasing need for molecular tools for analysis of a wide diversity of microorganisms. Currently, biological study of many prokaryotes of agricultural, medical, and fundamental scientific interest is limited by the lack of adequate genetic tools. We report the application of the bacterial artificial chromosome (BAC) vector to prokaryotic biology as a powerful approach to address this need. We constructed a BAC library in Escherichia coli from genomic DNA of the Gram-positive bacterium Bacillus cereus. This library provides 5.75-fold coverage of the B. cereus genome, with an average insert size of 98 kb. To determine the extent of heterologous expression of B. cereus genes in the library, we screened it for expression of several B. cereus activities in the E. coli host. Clones expressing 6 of 10 activities tested were identified in the library, namely, ampicillin resistance, zwittermicin A resistance, esculin hydrolysis, hemolysis, orange pigment production, and lecithinase activity. We analyzed selected BAC clones genetically to identify rapidly specific B. cereus loci. These results suggest that BAC libraries will provide a powerful approach for studying gene expression from diverse prokaryotes.

Identification of diverse nerve growth factor-regulated genes by serial analysis of gene expression (SAGE) profiling

Neurotrophic factors such as nerve growth factor (NGF) promote a wide variety of responses in neurons, including differentiation, survival, plasticity, and repair. Such actions often require changes in gene expression. To identify the regulated genes and thereby to more fully understand the NGF mechanism, we carried out serial analysis of gene expression (SAGE) profiling of transcripts derived from rat PC12 cells before and after NGF-promoted neuronal differentiation. Multiple criteria supported the reliability of the profile. Approximately 157,000 SAGE tags were analyzed, representing at least 21,000 unique transcripts. Of these, nearly 800 were regulated by 6-fold or more in response to NGF. Approximately 150 of the regulated transcripts have been matched to named genes, the majority of which were not previously known to be NGF-responsive. Functional categorization of the regulated genes provides insight into the complex, integrated mechanism by which NGF promotes its multiple actions. It is anticipated that as genomic sequence information accrues the data derived here will continue to provide information about neurotrophic factor mechanisms.

Saccharomyces Genome Database provides tools to survey gene expression and functional analysis data

Upon the completion of the Saccharomyces cerevisiae genomic sequence in 1996 [Goffeau,A. et al. (1997) Nature, 387, 5], several creative and ambitious projects have been initiated to explore the functions of gene products or gene expression on a genome-wide scale. To help researchers take advantage of these projects, the Saccharomyces Genome Database (SGD) has created two new tools, Function Junction and Expression Connection. Together, the tools form a central resource for querying multiple large-scale analysis projects for data about individual genes. Function Junction provides information from diverse projects that shed light on the role a gene product plays in the cell, while Expression Connection delivers information produced by the ever-increasing number of microarray projects. WWW access to SGD is available at genome-www.stanford.edu/Saccharomyces/.

High-sensitivity array analysis of gene expression for the early detection of disseminated breast tumor cells in peripheral blood

Early detection is an effective means of reducing cancer mortality. Here, we describe a highly sensitive high-throughput screen that can identify panels of markers for the early detection of solid tumor cells disseminated in peripheral blood. The method is a two-step combination of differential display and high-sensitivity cDNA arrays. In a primary screen, differential display identified 170 candidate marker genes differentially expressed between breast tumor cells and normal breast epithelial cells. In a secondary screen, high-sensitivity arrays assessed expression levels of these genes in 48 blood samples, 22 from healthy volunteers and 26 from breast cancer patients. Cluster analysis identified a group of 12 genes that were elevated in the blood of cancer patients. Permutation analysis of individual genes defined five core genes (P ≤ 0.05, permax test). As a group, the 12 genes generally distinguished accurately between healthy volunteers and patients with breast cancer. Mean expression levels of the 12 genes were elevated in 77% (10 of 13) untreated invasive cancer patients, whereas cluster analysis correctly classified volunteers and patients (P = 0.0022, Fisher's exact test). Quantitative real-time PCR confirmed array results and indicated that the sensitivity of the assay (1:2 × 108 transcripts) was sufficient to detect disseminated solid tumor cells in blood. Expression-based blood assays developed with the screening approach described here have the potential to detect and classify solid tumor cells originating from virtually any primary site in the body.