Abstract: BACKGROUND: Biological pathways are a useful abstraction of biological concepts, and software tools to deal with pathway diagrams can help biological research. PathVisio is a new visualization tool for biological pathways that mimics the popular GenMAPP tool with a completely new Java implementation that allows better integration with other open source projects. The GenMAPP MAPP file format is replaced by GPML, a new XML file format that provides seamless exchange of graphical pathway information among multiple programs. RESULTS: PathVisio can be combined with other bioinformatics tools to open up three possible uses: visual compilation of biological knowledge, interpretation of high-throughput expression datasets, and computational augmentation of pathways with interaction information. PathVisio is open source software and available at http://www.pathvisio.org. CONCLUSION: PathVisio is a graphical editor for biological pathways, with flexibility and ease of use as primary goals.
Abstract: BACKGROUND: High-throughput mutagenesis of the mammalian genome is a powerful means to facilitate analysis of gene function. Gene trapping in embryonic stem cells (ESCs) is the most widely used form of insertional mutagenesis in mammals. However, the rules governing its efficiency are not fully understood, and the effects of vector design on the likelihood of gene-trapping events have not been tested on a genome-wide scale. METHODOLOGY/PRINCIPAL FINDINGS: In this study, we used public gene-trap data to model gene-trap likelihood. Using the association of gene length and gene expression with gene-trap likelihood, we constructed spline-based regression models that characterize which genes are susceptible and which genes are resistant to gene-trapping techniques. We report results for three classes of gene-trap vectors, showing that both length and expression are significant determinants of trap likelihood for all vectors. Using our models, we also quantitatively identified hotspots of gene-trap activity, which represent loci where the high likelihood of vector insertion is controlled by factors other than length and expression. These formalized statistical models describe a high proportion of the variance in the likelihood of a gene being trapped by expression-dependent vectors and a lower, but still significant, proportion of the variance for vectors that are predicted to be independent of endogenous gene expression. CONCLUSIONS/SIGNIFICANCE: The findings of significant expression and length effects reported here further the understanding of the determinants of vector insertion. Results from this analysis can be applied to help identify other important determinants of this important biological phenomenon and could assist planning of large-scale mutagenesis efforts.
Abstract: BACKGROUND: Microarray technologies have evolved rapidly, enabling biologists to quantify genome-wide levels of gene expression, alternative splicing, and sequence variations for a variety of species. Analyzing and displaying these data present a significant challenge. Pathway-based approaches for analyzing microarray data have proven useful for presenting data and for generating testable hypotheses. RESULTS: To address the growing needs of the microarray community we have released version 2 of Gene Map Annotator and Pathway Profiler (GenMAPP), a new GenMAPP database schema, and integrated resources for pathway analysis. We have redesigned the GenMAPP database to support multiple gene annotations and species as well as custom species database creation for a potentially unlimited number of species. We have expanded our pathway resources by utilizing homology information to translate pathway content between species and extending existing pathways with data derived from conserved protein interactions and coexpression. We have implemented a new mode of data visualization to support analysis of complex data, including time-course, single nucleotide polymorphism (SNP), and splicing. GenMAPP version 2 also offers innovative ways to display and share data by incorporating HTML export of analyses for entire sets of pathways as organized web pages. CONCLUSION: GenMAPP version 2 provides a means to rapidly interrogate complex experimental data for pathway-level changes in a diverse range of organisms.
Abstract: Cytoscape is a free software package for visualizing, modeling and analyzing molecular and genetic interaction networks. This protocol explains how to use Cytoscape to analyze the results of mRNA expression profiling, and other functional genomics and proteomics experiments, in the context of an interaction network obtained for genes of interest. Five major steps are described: (i) obtaining a gene or protein network, (ii) displaying the network using layout algorithms, (iii) integrating with gene expression and other functional attributes, (iv) identifying putative complexes and functional modules and (v) identifying enriched Gene Ontology annotations in the network. These steps provide a broad sample of the types of analyses performed by Cytoscape.
Abstract: Although microarray technology has emerged as a powerful tool to explore expression levels of thousands of genes or even complete genomes after exposure to toxicants, the functional interpretation of microarray data sets still represents a time-consuming and challenging task. Gene ontology (GO) and pathway mapping have both been shown to be powerful approaches to generate a global view of biological processes and cellular components impacted by toxicants. However, current methods only allow for comparisons across two experimental settings at one particular time point. In addition, the resulting annotations are presented in extensive gene lists with minimal or limited quantitative information, data that are crucial in the application of toxicogenomic data for risk assessment. To facilitate quantitative interpretation of dose- or time-dependent genomic data, we propose to use combined average raw gene expression values (e.g., intensity or ratio) of genes associated with specific functional categories derived from the GO database. We developed an extended program (GO-Quant) to extract quantitative gene expression values and to calculate the average intensity or ratio for those significantly altered by functional gene category based on MAPPFinder results. To demonstrate its application, we applied this approach to a previously published dose- and time-dependent toxicogenomic data set (J. F. Dillman et al., 2005, Chem. Res. Toxicol. 18, 28-34). Our results indicate that the above systems approach can describe quantitatively the degree to which functional gene systems change across dose or time. Additionally, this approach provides a robust measurement to illustrate results compared to single-gene assessments and enables the user to calculate the corresponding ED(50) for each specific functional GO term, important for risk assessment.
Abstract: BACKGROUND: The most widely used amplification method for microarray analysis of gene expression uses T7 RNA polymerase-driven in vitro transcription (IVT) to produce complementary RNA (cRNA) that can be hybridized to arrays. However, multiple rounds of amplification are required when assaying very small amounts of starting RNA. Moreover, certain cRNA-DNA mismatches are more stable than the analogous cDNA-DNA mismatches and this might increase non-specific hybridization. We sought to determine whether a recently developed linear isothermal amplification method (ribo-SPIA) that produces single stranded cDNA would offer advantages over traditional IVT-based methods for microarray-based analyses of transcript expression. RESULTS: A single round of ribo-SPIA amplification produced sufficient sscDNA for hybridizations when as little as 5 ng of starting total RNA was used. Comparisons of probe set signal intensities obtained from replicate amplifications showed consistently high correlations (r = 0.99). We compared gene expression in two different human RNA samples using ribo-SPIA. Compared with one round IVT, ribo-SPIA had a larger dynamic range and correlated better with quantitative PCR results even though we used 1000-fold less starting RNA. The improved dynamic range was associated with decreases in hybridization to mismatch control probes. CONCLUSION: The use of amplified sscDNA may offer substantial advantages over IVT-based amplification methods, especially when very limited amounts of starting RNA are available. The use of sscDNA targets instead of cRNA targets appears to improve hybridization specificity.
Abstract: To develop a comprehensive catalogue of phenotypic and functional parameters of human CD4(+) T cell differentiation stages, we have performed microarray gene expression profiling on subpopulations of human thymocytes and circulating naive CD4(+) T cells, including CD3(-)CD4(+)CD8(-) intrathymic T progenitor cells, CD3(int)CD4(+)CD8(+) 'double positive' thymocytes, CD3(high)CD4(+)CD8(-) 'single positive' thymocytes, CD3(+)CD4(+)CD8(-) CD45RA(+)CD62L(+) naive T cells from cord blood and CD3(+)CD4(+)CD8(-) CD45RA(+)CD62L(+) naive T cells from adult blood. These subpopulations were sort-purified to >98% purity and their expressed RNAs were analyzed on Affymetrix Human Genome U133 arrays. Comparison of gene expression signals between these subpopulations and with early passage fetal thymic stromal cultures identify: (i) transcripts that are preferentially expressed in human CD4(+) T cell subpopulations and not in thymic stromal cells; (ii) major shifts in gene expression as progenitor T cells mature into progeny; (iii) preferential expression of transcripts at the progenitor cell stage with plausible relevance to the regulation of expansion and differentiation of these cells; and (iv) preferential expression of potential markers of recent thymic emigrants in naive-phenotype CD4(+) T cells from cord blood. Further evaluation of these findings may lead to a better definition of human thymopoiesis as well as to improved approaches to monitor and to augment the function of this important organ of T cell production.
Abstract: DNA microarrays produced by deposition (or 'spotting')of a single long oligonucleotide probe for each gene may be an attractive alternative to other types of arrays. We produced spotted oligonucleotide arrays using two large collections of approximately 70-mer probes, and used these arrays to analyze gene expression in two dissimilar human RNA samples. These samples were also analyzed using arrays produced by in situ synthesis of sets of multiple short (25-mer) oligonucleotides for each gene (Affymetrix GeneChips). We compared expression measurements for 7344 genes that were represented in both long oligonucleotide probe collections and the in situ-synthesized 25-mer arrays. We found strong correlations (r = 0.8-0.9) between relative gene expression measurements made with spotted long oligonucleotide probes and in situ-synthesized 25-mer probe sets. Spotted long oligonucleotide arrays were suitable for use with both unamplified cDNA and amplified RNA targets, and are a cost-effective alternative for many functional genomics applications. Most previously reported evaluations of microarray technologies have focused on expression measurements made on a relatively small number of genes. The approach described here involves far more gene expression measurements and provides a useful method for comparing existing and emerging techniques for genome-scale expression analysis.
Abstract: Sulfatide (3'sulfogalactosylceramide) is a glycosphingolipid present within the nervous system and in the islets of Langerhans. Anti-sulfatide antibodies have been observed in both pre-diabetic and newly diagnosed type 1 diabetic patients. The aim of this study was to test in vivo, the therapeutic effect of sulfatide on the development of diabetes in the NOD mouse. In four separate experiments diabetogenic splenocytes from newly diabetic NOD mice were injected iv into 7-8 week old irradiated (700R) female NOD mice (4-10 million cells/mouse). Each experiment consisted of four treatment groups to which the mice were randomly divided: 1) sulfatide; 2) galactosylceramide (the precursor to sulfatide without sulfate); 3) GM1, a glycosphingolipid negatively charged as sulfatide but with a different sugar composition; and 4) phosphate buffered saline (PBS). The mice received 100 microg glycosphingolipid iv on the day of cell transfer and 1-3 times thereafter at four day intervals, and were screened for diabetes three times a week the next 52 days. Among all the 35 sulfatide-treated mice 54% became diabetic compared to 93 % of 43 PBS-treated animals (p < 0.00001). Correspondingly, galactosylceramide reduced diabetes incidence to 52% (25 mice, p < 0.00001). On the other hand, 86% of GM1-treated mice (n=28) became diabetic indicating that no effect was obtained by this glycosphingolipid. In two experiments in which less spleen cells were transferred (4-5 mill.) and glycosphingolipids were given 4 times, 35% of the sulfatide-treated animals (n = 17) developed diabetes compared to 85% of PBS-treated mice (n = 20, p < 0.001). A robust proliferative response to sulfatide, but none to GM1, was observed when spleen cells were rechallenged with glycosphingolipid in vitro. Thus, like insulin and GAD, sulfatide is able to prevent diabetes in NOD mice.
