GeneComps and ChemComps: a new CTD metric to identify genes and chemicals with shared toxicogenomic profiles

The Comparative Toxicogenomics Database is a public resource that promotes understanding about the effects of environmental chemicals on human health. Currently, CTD describes over 184,000 molecular interactions for more than 5,100 chemicals and 16,300 genes/proteins. We have leveraged this dataset of chemical-gene relationships to compute similarity indices following the statistical method of the Jaccard index. These scores are used to produce lists of comparable genes (“GeneComps”) or chemicals (“ChemComps”) based on shared toxicogenomic profiles. GeneComps and ChemComps are now provided for every curated gene and chemical in CTD. ChemComps are particularly significant because they provide a way to group chemicals based upon their biological effects, instead of their physical or structural properties. These metrics provide a novel way to view and classify genes and chemicals and will help advance testable hypotheses about environmental chemical-genedisease networks.

Availability

CTD is freely available at http://ctd.mdibl.org/     

Tools for assessing European streams with macroinvertebrates: major results and conclusions from the STAR project

This short paper summarises the information developed in the EU funded research project STAR on autecology databases, metrics, multimetrics and community approaches. For Europe the WFD implementation gave an important stimulus for the development of ecology based assessment techniques. Along with the development of metrics and multimetrics indices taxalists and autecological information were strongly improved. Recommendations are given to further develop ecological assessment in European streams and rivers.     

RADAR,a relational archaeobotanical database for advanced research

The structure of the Dutch Relational Archaeobotanical Database (RADAR) is presented. RADAR is a rather compact archaeobotanical database that is controlled centrally, but can be distributed to individual scientists. For this reason RADAR contains only the most important archaeobotanical data. For detailed archaeological, botanical and regional palaeoenvironmental information, links can be established with the national archaeological database (ARCHIS), the national botanical database (BBR) and the European Pollen Database (EPD). The software used for manipulation of the database is PARADOX for reasons of its highly visible nature, its control facilities for data entry and the ease of importing and exporting data from and to many other programs. The potential of the database is demonstrated with query examples.     

SNPs in the porcine <Emphasis Type="Italic">PPARGC1a</Emphasis> gene: Interbreed differences and their phenotypic effects

Due to its function, the peroxisome proliferative activated receptor-γ, coactivator-1α (PPARGC1A) gene is a candidate in the search for genes that may affect production traits in the pig. The purpose of this study was to screen for new SNPs in exon 8 of the porcine PPARGC1A gene and to test their possible association with production traits. Altogether 736 pigs representing five breeds Polish Landrace, n=242; Polish Large White, n=192; Hampshire, n=27; Duroc, 21; Pietrain, n=12) and synthetic line 990 (n=242) were scanned via SSCP assay. Four SNPs were found; two new ones: C/G (His338Gln) and G/A Thr359Thr), and two previously reported ones: C/A (Arg369Arg) and T/A Cys430Ser). The missense T/A and C/G SNPs demonstrated pronounced interbreed variability in terms of allele frequencies, including the exclusive presence of the C/G substitution in the Hampshire breed. The tested SNPs occurred in five putative haplotypes, and their frequency also differed substantially between breeds. The association of the SNPs with production traits was tested for G/A (Thr359Thr), C/A (Arg369Arg) and T/A (Cys430Ser) substitutions in Polish Large White, Polish Landrace and line 990. The analysis revealed only breed-specific associations. The T/A (Cys430Ser) SNP was related to the feed conversion ratio in the Polish Large White (P=0.02), and the silent G/A and C/A substitutions were respectively associated with abdominal fat in line 990 and backfat thickness in Polish Landrace (P=0.04). The combined effects of the substitutions were estimated as haplotype effects. Three significant contrasts between haplotypes were calculated, but the observed associations were again only breed-specific.     

Conversion of AFLP markers to sequence-specific markers for closely related lines in rice by use of the rice genome sequence

DNA polymorphism between two major japonica rice cultivars, Nipponbare and Koshihikari, was identified by AFLP. Eighty-four polymorphic AFLP markers were obtained by analysis with 360 combinations of primer pairs. Nucleotide sequences of 73 markers, 29 from Nipponbare and 44 from Koshihikari, were determined, and 46 AFLP markers could be assigned to rice chromosomes based on sequence homology to the rice genome sequence. Specific primers were designed for amplification of the regions covering the AFLP markers and the flanking sequences. Out of the 46 primer pairs, 44 amplified single DNA fragments, six of which showed different sizes between Nipponbare and Koshihikari, yielding codominant SCAR markers. Eight primer pairs amplified only Nipponbare sequences, providing dominant SCAR markers. DNA fragments amplified by 13 primer pairs showed polymorphism by CAPS, and polymorphism of those amplified by 13 other primer pairs were detected by PCR-RF-SSCP (PRS). Nucleotide sequences of the other four DNA fragments were determined in Koshihikari, but no difference was found between Koshihikari and Nipponbare. In total, 40 sequence-specific markers for the combination of Nipponbare and Koshihikari were produced. All the SNPs identified by AFLP were detectable by CAPS and PRS. The same method was applicable to a combination of Kokoromachi and Tohoku 168, and 23 polymorphic markers were identified using these two rice cultivars. The procedure of conversion of AFLP-markers to the sequence-specific markers used in this study enables efficient sequence-specific marker production for closely related cultivars.