Logical Operation Based Literature Association with Genes and its application, PosMed.

PosMed prioritizes candidate genes for positional cloning by employing our original database search engine GRASE, which uses an inferential process similar to an artificial neural network comprising documental neurons (or 'documentrons') that represent each document contained in databases such as MEDLINE and OMIM (Yoshida, _et al_. 2009, Makita, _et al_. 2009). PosMed immediately ranks the candidate genes by connecting phenotypic keywords to the genes through connections representing gene–gene interactions other biological relationships, such as metabolite–gene, mutant mouse–gene, drug–gene, disease–gene, and protein–protein interactions, ortholog data, and gene–literature connections.

To make proper relationships between genes and literature, we manually curate queries, which are defined by logical operation rules, against MEDLINE. For example, to detect a set of MEDLINE documents for the AT1G03880 gene in _A. thaliana_, we applied the following logical query: (‘AT1G03880’ OR ‘CRU2’ OR ‘CRB’ OR ‘CRUCIFERIN 2' OR ‘CRUCIFERIN B’) AND (‘Arabidopsis’) NOT (‘chloroplast RNA binding’). Curators refined these queries in mouse, rice and _A. thaliana_. For human and rat genes, we use mouse curation results via ortholog genes in PosMed.

PosMed is available at "http://omicspace.riken.jp/PosMed":http://omicspace.riken.jp/PosMed

References:
Yoshida Y, et al. _Nucleic Acids Res_. 37(Web Server issue):W147-52. 2009. 
Makita Y, et al. _Plant Cell Physiol_. 2009 Jul;50(7):1249-59.
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Evaluation of wood preservatives against the drywood termite, Incisitermes minor

Tese de doutoramento em Arte Contemporânea, apresentada ao Colégio das Artes da Universidade de Coimbra

Melina II: a web tool for comparisons among several predictive algorithms to find potential motifs from promoter regions

We present the second version of Melina, a web-based tool for promoter analysis. Melina II shows potential DNA motifs in promoter regions with a combination of several available programs, Consensus, MEME, Gibbs sampler, MDscan and Weeder, as well as several parameter settings. It allows running a maximum of four programs simultaneously, and comparing their results with graphical representations. In addition, users can build a weight matrix from a predicted motif and apply it to upstream sequences of several typical genomes (human, mouse, S. cerevisiae, E. coli, B. subtilis or A. thaliana) or to public motif databases (JASPAR or DBTBS) in order to find similar motifs. Melina II is a client/server system developed by using Adobe (Macromedia) Flash and is accessible over the web at http://melina.hgc.jp

Hon-yaku: a biology-driven Bayesian methodology for identifying translation initiation sites in prokaryotes

Background: Computational prediction methods are currently used to identify genes in prokaryote genomes. However, identification of the correct translation initiation sites remains a difficult task. Accurate translation initiation sites (TISs) are important not only for the annotation of unknown proteins but also for the prediction of operons, promoters, and small non-coding RNA genes, as this typically makes use of the intergenic distance. A further problem is that most existing methods are optimized for Escherichia coli data sets; applying these methods to newly sequenced bacterial genomes may not result in an equivalent level of accuracy. Results: Based on a biological representation of the translation process, we applied Bayesian statistics to create a score function for predicting translation initiation sites. In contrast to existing programs, our combination of methods uses supervised learning to optimally use the set of known translation initiation sites. We combined the Ribosome Binding Site (RBS) sequence, the distance between the translation initiation site and the RBS sequence, the base composition of the start codon, the nucleotide composition (A-rich sequences) following start codons, and the expected distribution of the protein length in a Bayesian scoring function. To further increase the prediction accuracy, we also took into account the operon orientation. The outcome of the procedure achieved a prediction accuracy of 93.2% in 858 E. coli genes from the EcoGene data set and 92.7% accuracy in a data set of 1243 Bacillus subtilis 'non-y' genes. We confirmed the performance in the GC-rich Gamma-Proteobacteria Herminiimonas arsenicoxydans, Pseudomonas aeruginosa, and Burkholderia pseudomallei K96243. Conclusion: Hon-yaku, being based on a careful choice of elements important in translation, improved the prediction accuracy in B. subtilis data sets and other bacteria except for E. coli. We believe that most remaining mispredictions are due to atypical ribosomal binding sequences used in specific translation control processes, or likely errors in the training data sets

DBTBS: a database of transcriptional regulation in Bacillus subtilis containing upstream intergenic conservation information

DBTBS, first released in 1999, is a reference database on transcriptional regulation in Bacillus subtilis, summarizing the experimentally characterized transcription factors, their recognition sequences and the genes they regulate. Since the previous release, the original content was extended by the addition of the data contained in 569 new publications, the total of which now reaches 947. The number of B. subtilis promoters annotated in the database was more than doubled to 1475. In addition, 463 experimentally validated B. subtilis operons and their terminators have been included. Given the increase in the number of fully sequenced bacterial genomes, we decided to extend the usability of DBTBS in comparative regulatory genomics. We therefore created a new section on the conservation of the upstream regulatory sequences between homologous genes in 40 Gram-positive bacterial species, as well as on the presence of overrepresented hexameric motifs that may have regulatory functions. DBTBS can be accessed at: http://dbtbs.hgc.jp

A Panel of Serum Biomarkers Differentiates IgA Nephropathy from Other Renal Diseases

Background and Objectives: There is increasing evidence that galactose-deficient IgA1 (Gd-IgA1) and Gd-IgA1-containing immune complexes are important for the pathogenesis of IgA nephropathy (IgAN). In the present study, we assessed a novel noninvasive multi-biomarker approach in the diagnostic test for IgAN. Materials and Methods: We compared serum levels of IgA, IgG, Gd-IgA1, Gd-IgA1-specific IgG and Gd-IgA1-specific IgA in 135 IgAN patients, 79 patients with non-IgAN chronic kidney disease (CKD) controls and 106 healthy controls. Serum was collected at the time of kidney biopsy from all IgAN and CKD patients. Results: Each serum marker was significantly elevated in IgAN patients compared to CKD (P<0.001) and healthy controls (P<0.001). While 41% of IgAN patients had elevated serum Gd-IgA1 levels, 91% of these patients exhibited Gd-IgA1-specific IgG levels above the 90th percentile for healthy controls (sensitivity 89%, specificity 92%). Although up to 25% of CKD controls, particularly those with immune-mediated glomerular diseases including lupus nephritis, also had elevated serum levels of Gd-IgA1-specific IgG, most IgAN patients had elevated levels of Gd-IgA1-specific antibody of both isotypes. Serum levels of Gd-IgA1-specific IgG were associated with renal histological grading. Furthermore, there was a trend toward higher serum levels of Gd-IgA1-specific IgG in IgAN patients with at least moderate proteinuria (≥1.0 g/g), compared to patients with less proteinuria. Conclusions Serum levels of Gd-IgA1-specific antibodies are elevated in most IgAN patients, and their assessment, together with serum levels of Gd-IgA1, improves the specificity of the assays. Our observations suggest that a panel of serum biomarkers may be helpful in differentiating IgAN from other glomerular diseases

Identifying the target genes of SUPPRESSOR OF GAMMA RESPONSE 1, a master transcription factor controlling DNA damage response in Arabidopsis

In mammalian cells, the transcription factor p53 plays a crucial role in transmitting DNA damage signals to maintain genome integrity. However, in plants, orthologous genes for p53 and checkpoint proteins are absent. Instead, the plant-specific transcription factor SUPPRESSOR OF GAMMA RADIATION 1 (SOG1) controls most of the genes induced by gamma irradiation and promotes DNA repair, cell cycle arrest, and stem cell death. Thus far, the genes directly controlled by SOG1 remain largely unknown, limiting the understanding of DNA damage signaling in plants. Here, we conducted a microarray analysis and chromatin immunoprecipitation (ChIP)-sequencing, and identified 146 Arabidopsis genes as direct targets of SOG1. By using the ChIP-sequencing data, we extracted the palindromic motif [CTT(N)7AAG] as a consensus SOG1-binding sequence, which mediates target gene induction in response to DNA damage. Furthermore, DNA damage-triggered phosphorylation of SOG1 is required for efficient binding to SOG1-binding sequence. Comparison between SOG1 and p53 target genes showed that both transcription factors control genes responsible for cell cycle regulation, such as CDK inhibitors, and DNA repair proteins, whereas SOG1 preferentially targets genes involved in homologous recombination. We also found that defense-related genes were enriched in the SOG1 target genes. Consistent with this, SOG1 is required for resistance against the hemi-biotrophic fungus Colletotrichum higginsianum, suggesting that SOG1 has a unique function in controlling immune response. This article is protected by copyright. All rights reserved

Prediction of Transcriptional Terminators in Bacillus subtilis and Related Species

In prokaryotes, genes belonging to the same operon are transcribed in a single mRNA molecule. Transcription starts as the RNA polymerase binds to the promoter and continues until it reaches a transcriptional terminator. Some terminators rely on the presence of the Rho protein, whereas others function independently of Rho. Such Rho-independent terminators consist of an inverted repeat followed by a stretch of thymine residues, allowing us to predict their presence directly from the DNA sequence. Unlike in Escherichia coli, the Rho protein is dispensable in Bacillus subtilis, suggesting a limited role for Rho-dependent termination in this organism and possibly in other Firmicutes. We analyzed 463 experimentally known terminating sequences in B. subtilis and found a decision rule to distinguish Rho-independent transcriptional terminators from non-terminating sequences. The decision rule allowed us to find the boundaries of operons in B. subtilis with a sensitivity and specificity of about 94%. Using the same decision rule, we found an average sensitivity of 94% for 57 bacteria belonging to the Firmicutes phylum, and a considerably lower sensitivity for other bacteria. Our analysis shows that Rho-independent termination is dominant for Firmicutes in general, and that the properties of the transcriptional terminators are conserved. Terminator prediction can be used to reliably predict the operon structure in these organisms, even in the absence of experimentally known operons. Genome-wide predictions of Rho-independent terminators for the 57 Firmicutes are available in the Supporting Information section

PosMed: ranking genes and bioresources based on Semantic Web Association Study

ABSTRACT Positional MEDLINE (PosMed; http://biolo