Glia Open Access Database (GOAD): A comprehensive gene expression encyclopedia of glia cells in health and disease.

Recently, the number of genome-wide transcriptome profiles of pure populations of glia cells has drastically increased, resulting in an unprecedented amount of data that offer opportunities to study glia phenotypes and functions in health and disease. To make genome-wide transcriptome data easily accessible, we developed the Glia Open Access Database (GOAD), available via www.goad.education. GOAD contains a collection of previously published and unpublished transcriptome data, including datasets from isolated microglia, astrocytes and oligodendrocytes both at homeostatic and pathological conditions. It contains an intuitive web-based interface that consists of three features that enable searching, browsing, analyzing, and downloading of the data. The first feature is differential gene expression (DE) analysis that provides genes that are significantly up and down-regulated with the associated fold changes and p-values between two conditions of interest. In addition, an interactive Venn diagram is generated to illustrate the overlap and differences between several DE gene lists. The second feature is quantitative gene expression (QE) analysis, to investigate which genes are expressed in a particular glial cell type and to what degree. The third feature is a search utility, which can be used to find a gene of interest and depict its expression in all available expression data sets by generating a gene card. In addition, quality guidelines and relevant concepts for transcriptome analysis are discussed. Finally, GOAD is discussed in relation to several online transcriptome tools developed in neuroscience and immunology. In conclusion, GOAD is a unique platform to facilitate integration of bioinformatics in glia biology.

Fast selection of miRNA candidates based on large-scale pre-computed MFE sets of randomized sequences.

BACKGROUND: Small RNAs are important regulators of genome function, yet their prediction in genomes is still a major computational challenge. Statistical analyses of pre-miRNA sequences indicated that their 2D structure tends to have a minimal free energy (MFE) significantly lower than MFE values of equivalently randomized sequences with the same nucleotide composition, in contrast to other classes of non-coding RNA. The computation of many MFEs is, however, too intensive to allow for genome-wide screenings. RESULTS: Using a local grid infrastructure, MFE distributions of random sequences were pre-calculated on a large scale. These distributions follow a normal distribution and can be used to determine the MFE distribution for any given sequence composition by interpolation. It allows on-the-fly calculation of the normal distribution for any candidate sequence composition. CONCLUSION: The speedup achieved makes genome-wide screening with this characteristic of a pre-miRNA sequence practical. Although this particular property alone will not be able to distinguish miRNAs from other sequences sufficiently discriminative, the MFE-based P-value should be added to the parameters of choice to be included in the selection of potential miRNA candidates for experimental verification.

The 172 kb prkA-addAB region from 83 degrees to 97 degrees of the Bacillus subtilis chromosome contains several dysfunctional genes, the glyB marker, many genes encoding transporter proteins, and the ubiquitous hit gene.

A 171812 bp nucleotide sequence between prkA and addAB (83 degrees to 97 degrees) on the genetic map of the Bacillus subtilis 168 chromosome was determined and analysed. An accurate physical/genetic map of this previously poorly described chromosomal region was constructed. One hundred and seventy open reading frames (ORFs) were identified on the DNA fragment. These include the previously described genes cspB, glpPFKD, spoVR, phoAIV, papQ, citRA, sspB, prsA, hpr, pbpF, hemEHY, aprE, comK and addAB. ORF yhaF in this region corresponds to the glyB marker. Among the striking features of this region are: an abundance of genes encoding (putative) transporter proteins, several dysfunctional genes, the ubiquitous hit gene, and five multidrug-resistance-like genes. These analyses have also revealed the existence of numerous paralogues of ORFs in this region: about two-thirds of the putative genes seem to have at least one paralogue in the B. subtilis genome.