PaLS: filtering common literature, biological terms and pathway information

Many biological experiments and their subsequent analysis yield lists of genes or proteins that can potentially be important to the prognosis or diagnosis of certain diseases (e.g. cancer). Nowadays, information about the function of those genes or proteins may be already gathered in some databases, but it is essential to understand if some of the members of those lists have a function in common or if they belong to the same metabolic pathway. To help researchers filter those genes or proteins that have such information in common, we have developed PaLS (pathway and literature strainer, http://pals.bioinfo.cnio.es). PaLS takes a list or a set of lists of gene or protein identifiers and shows which ones share certain descriptors. Four publicly available databases have been used for this purpose: PubMed, which links genes with those articles that make reference to them; Gene Ontology, an annotated ontology of terms related to the cellular component, biological process or molecular function where those genes or proteins are involved; KEGG pathways and Reactome pathways. Those descriptors among these four sources of information that are shared by more members of the list (or lists) are highlighted by PaLS

The Chemical Evolution of Magnesium Isotopic Abundances in the Solar Neighbourhood

The abundance of the neutron-rich magnesium isotopes observed in metal-poor stars is explained quantitatively with a chemical evolution model of the local Galaxy that considers - for the first time - the metallicity-dependent contribution from intermediate mass stars. Previous models that simulate the variation of Mg isotopic ratios with metallicity in the solar neighbourhood have attributed the production of Mg25 and Mg26 exclusively to hydrostatic burning in massive stars. These models match the data well for [Fe/H]>-1.0 but severely underestimate Mg25/Mg24 and Mg26/Mg24 at lower metallicities. Earlier studies have noted that this discrepancy may indicate a significant role played by intermediate-mass stars. Only recently have detailed calculations of intermediate-mass stellar yields of Mg25 and Mg26 become available with which to test this hypothesis. In an extension of previous work, we present a model that successfully matches the Mg isotopic abundances in nearby Galactic disk stars through the incorporation of nucleosynthesis predictions of Mg isotopic production in asymptotic giant branch stars.Comment: 9 pages, 6 figures, to appear in Publications of the Astronomical Society of Australia (PASA) in 2003, vol. 20, No.

ERGR: An ethanol-related gene resource

Over the last decade rapid progress has been made in the study of ethanol-related traits including alcohol abuse and dependence, and behavioral responses to ethanol in both humans and animal models. To collect, curate, integrate these results so as to make them easily accessible and interpretable for researchers, we developed ERGR, a comprehensive ethanol-related gene resource. We collected and curated more than 30 large-scale data sets including linkage, association and microarray gene expression from the literature and 21 mouse QTLs from public databases. At present, the ERGR deposits ethanol-related information of ∼7000 genes from five organisms: human (3311), mouse (2129), rat (679), fly (614) and worm (228). ERGR provides gene annotations and orthologs, detailed gene study information (e.g. fold changes of gene expression, P-values), and both the text and BLAST searches. Moreover, ERGR has data integration tools such as for data union and intersection, and candidate gene selection based on evidence in multiple datasets or organisms. The ERGR database is evolving with new data releases. More functions will also be added. ERGR has a user-friendly web interface with browse and search functions at multiple levels. It is freely available at http://bioinfo.vipbg.vcu.edu/ERGR/

Deep Sequencing Reveals Direct Targets of Gammaherpesvirus-Induced mRNA Decay and Suggests That Multiple Mechanisms Govern Cellular Transcript Escape

One characteristic of lytic infection with gammaherpesviruses, including Kaposi's sarcoma-associated herpesvirus (KSHV), Epstein-Barr virus (EBV) and murine herpesvirus 68 (MHV68), is the dramatic suppression of cellular gene expression in a process known as host shutoff. The alkaline exonuclease proteins (KSHV SOX, MHV-68 muSOX and EBV BGLF5) have been shown to induce shutoff by destabilizing cellular mRNAs. Here we extend previous analyses of cellular mRNA abundance during lytic infection to characterize the effects of SOX and muSOX, in the absence of other viral genes, utilizing deep sequencing technology (RNA-seq). Consistent with previous observations during lytic infection, the majority of transcripts are downregulated in cells expressing either SOX or muSOX, with muSOX acting as a more potent shutoff factor than SOX. Moreover, most cellular messages fall into the same expression class in both SOX- and muSOX-expressing cells, indicating that both factors target similar pools of mRNAs. More abundant mRNAs are more efficiently downregulated, suggesting a concentration effect in transcript targeting. However, even among highly expressed genes there are mRNAs that escape host shutoff. Further characterization of select escapees reveals multiple mechanisms by which cellular genes can evade downregulation. While some mRNAs are directly refractory to SOX, the steady state levels of others remain unchanged, presumably as a consequence of downstream effects on mRNA biogenesis. Collectively, these studies lay the framework for dissecting the mechanisms underlying the susceptibility of mRNA to destruction during lytic gammaherpesvirus infection

INTERFEROME: the database of interferon regulated genes.

INTERFEROME is an open access database of types I, II and III Interferon regulated genes (http://www.interferome.org) collected from analysing expression data sets of cells treated with IFNs. This database of interferon regulated genes integrates information from high-throughput experiments with annotation, ontology, orthologue sequences from 37 species, tissue expression patterns and gene regulatory information to enable a detailed investigation of the molecular mechanisms underlying IFN biology. INTERFEROME fulfils a need in infection, immunity, development and cancer research by providing computational tools to assist in identifying interferon signatures in gene lists generated by high-throughput expression technologies, and their potential molecular and biological consequences

MicroRNA-224 Targets SMAD Family Member 4 to Promote Cell Proliferation and Negatively Influence Patient Survival

10.1371/journal.pone.0068744PLoS ONE87-POLN

Notch and MAML-1 Complexation Do Not Detectably Alter the DNA Binding Specificity of the Transcription Factor CSL

Canonical Notch signaling is initiated when ligand binding induces proteolytic release of the intracellular part of Notch (ICN) from the cell membrane. ICN then travels into the nucleus where it drives the assembly of a transcriptional activation complex containing the DNA-binding transcription factor CSL, ICN, and a specialized co-activator of the Mastermind family. A consensus DNA binding site motif for the CSL protein was previously defined using selection-based methods, but whether subsequent association of Notch and Mastermind-like proteins affects the DNA binding preferences of CSL has not previously been examined.Here, we utilized protein-binding microarrays (PBMs) to compare the binding site preferences of isolated CSL with the preferred binding sites of CSL when bound to the CSL-binding domains of all four different human Notch receptors. Measurements were taken both in the absence and in the presence of Mastermind-like-1 (MAML1). Our data show no detectable difference in the DNA binding site preferences of CSL before and after loading of Notch and MAML1 proteins.These findings support the conclusion that accrual of Notch and MAML1 promote transcriptional activation without dramatically altering the preferred sites of DNA binding, and illustrate the potential of PBMs to analyze the binding site preferences of multiprotein-DNA complexes

Using a structural and logics systems approach to infer bHLH–DNA binding specificity determinants

Numerous efforts are underway to determine gene regulatory networks that describe physical relationships between transcription factors (TFs) and their target DNA sequences. Members of paralogous TF families typically recognize similar DNA sequences. Knowledge of the molecular determinants of protein–DNA recognition by paralogous TFs is of central importance for understanding how small differences in DNA specificities can dictate target gene selection. Previously, we determined the in vitro DNA binding specificities of 19 Caenorhabditis elegans basic helix-loop-helix (bHLH) dimers using protein binding microarrays. These TFs bind E-box (CANNTG) and E-box-like sequences. Here, we combine these data with logics, bHLH–DNA co-crystal structures and computational modeling to infer which bHLH monomer can interact with which CAN E-box half-site and we identify a critical residue in the protein that dictates this specificity. Validation experiments using mutant bHLH proteins provide support for our inferences. Our study provides insights into the mechanisms of DNA recognition by bHLH dimers as well as a blueprint for system-level studies of the DNA binding determinants of other TF families in different model organisms and humans.National Institute of General Medical Sciences (U.S.) (DK068429)National Institute of General Medical Sciences (U.S.) (HG003985)European Union (PROSPECTS HEALTH-F4-2008-201648

Towards a pathway definition of Parkinson’s disease: a complex disorder with links to cancer, diabetes and inflammation

We have previously established a first whole genome transcriptomic profile of sporadic Parkinson’s disease (PD). After extensive brain tissue-based validation combined with cycles of iterative data analysis and by focusing on the most comparable cases of the cohort, we have refined our analysis and established a list of 892 highly dysregulated priority genes that are considered to form the core of the diseased Parkinsonian metabolic network. The substantia nigra pathways, now under scrutiny, contain more than 100 genes whose association with PD is known from the literature. Of those, more than 40 genes belong to the highly significantly dysregulated group identified in our dataset. Apart from the complete list of 892 priority genes, we present pathways revealing PD ‘hub’ as well as ‘peripheral’ network genes. The latter include Lewy body components or interact with known PD genes. Biological associations of PD with cancer, diabetes and inflammation are discussed and interactions of the priority genes with several drugs are provided. Our study illustrates the value of rigorous clinico-pathological correlation when analysing high-throughput data to make optimal use of the histopathological phenome, or morphonome which currently serves as the key diagnostic reference for most human diseases. The need for systematic human tissue banking, following the highest possible professional and ethical standard to enable sustainability, becomes evident

Global Analysis of DNA Methylation by Methyl-Capture Sequencing Reveals Epigenetic Control of Cisplatin Resistance in Ovarian Cancer Cell

Cisplatin resistance is one of the major reasons leading to the high death rate of ovarian cancer. Methyl-Capture sequencing (MethylCap-seq), which combines precipitation of methylated DNA by recombinant methyl-CpG binding domain of MBD2 protein with NGS, global and unbiased analysis of global DNA methylation patterns. We applied MethylCap-seq to analyze genome-wide DNA methylation profile of cisplatin sensitive ovarian cancer cell line A2780 and its isogenic derivative resistant line A2780CP. We obtained 21,763,035 raw reads for the drug resistant cell line A2780CP and 18,821,061reads for the sensitive cell line A2780. We identified 1224 hyper-methylated and 1216 hypomethylated DMRs (differentially methylated region) in A2780CP compared to A2780. Our MethylCap-seq data on this ovarian cancer cisplatin resistant model provided a good resource for the research community. We also found that A2780CP, compared to A2780, has lower observed to expected methylated CpG ratios, suggesting a lower global CpG methylation in A2780CP cells. Methylation specific PCR and bisulfite sequencing confirmed hypermethylation of PTK6, PRKCE and BCL2L1 in A2780 compared with A2780CP. Furthermore, treatment with the demethylation reagent 5-aza-dC in A2780 cells demethylated the promoters and restored the expression of PTK6, PRKCE and BCL2L1