Biomedical subjects

Joke Allemeersch

Publications and source records attributed to Joke Allemeersch.

4 recordsLinked to original sources

PubMed2005

The effect of a sertoli cell-selective knockout of the androgen receptor on testicular gene expression in prepubertal mice.

To unravel the molecular mechanisms mediating the effects of androgens on spermatogenesis, testicular gene expression was compared in mice with Sertoli cell-selective androgen receptor knockout (SCARKO) and littermate controls on postnatal d 10. Microarray analysis identified 692 genes with significant differences in expression. Of these, 28 appeared to be down-regulated and 12 up-regulated at least 2-fold in SCARKOs compared with controls. For nine of the more than 2-fold down-regulated genes, androgen regulation was confirmed by treatment of wild-type mice with an antiandrogen (flutamide). Some of them were previously described to be androgen regulated or essential for spermatogenesis. Serine-type protease inhibitors were markedly overrepresented in this down-regulated subgroup. A time study (d 8-20), followed by cluster analysis, allowed identification of distinct expression patterns of differentially expressed genes. Three genes with a pattern closely resembling that of Pem, a prototypical androgen-regulated gene expressed in Sertoli cells, were selected for confirmation by quantitative RT-PCR and additional analysis. The data confirm that the SCARKO model allows identification of novel androgen-regulated genes in the testis. Moreover, they suggest that protease inhibitors and other proteins related to tubular restructuring and cell junction dynamics may be controlled in part by androgens.

Androgens↗

PubMed2005

Benchmarking the CATMA microarray. A novel tool for Arabidopsis transcriptome analysis.

Transcript profiling is crucial to study biological systems, and various platforms have been implemented to survey mRNAs at the genome scale. We have assessed the performance of the CATMA microarray designed for Arabidopsis (Arabidopsis thaliana) transcriptome analysis and compared it with the Agilent and Affymetrix commercial platforms. The CATMA array consists of gene-specific sequence tags of 150 to 500 bp, the Agilent (Arabidopsis 2) array of 60mer oligonucleotides, and the Affymetrix gene chip (ATH1) of 25mer oligonucleotide sets. We have matched each probe repertoire with the Arabidopsis genome annotation (The Institute for Genomic Research release 5.0) and determined the correspondence between them. Array performance was analyzed by hybridization with labeled targets derived from eight RNA samples made of shoot total RNA spiked with a calibrated series of 14 control transcripts. CATMA arrays showed the largest dynamic range extending over three to four logs. Agilent and Affymetrix arrays displayed a narrower range, presumably because signal saturation occurred for transcripts at concentrations beyond 1,000 copies per cell. Sensitivity was comparable for all three platforms. For Affymetrix GeneChip data, the RMA software package outperformed Microarray Suite 5.0 for all investigated criteria, confirming that the information provided by the mismatch oligonucleotides has no added value. In addition, taking advantage of replicates in our dataset, we conducted a robust statistical analysis of the platform propensity to yield false positive and false negative differentially expressed genes, and all gave satisfactory results. The results establish the CATMA array as a mature alternative to the Affymetrix and Agilent platforms.

Arabidopsis↗

PubMed2004

Importing MAGE-ML format microarray data into BioConductor.

UNLABELLED: The microarray gene expression markup language (MAGE-ML) is a widely used XML (eXtensible Markup Language) standard for describing and exchanging information about microarray experiments. It can describe microarray designs, microarray experiment designs, gene expression data and data analysis results. We describe RMAGEML, a new Bioconductor package that provides a link between cDNA microarray data stored in MAGE-ML format and the Bioconductor framework for preprocessing, visualization and analysis of microarray experiments. AVAILABILITY: http://www.bioconductor.org. Open Source.

Database Management Systems↗

PubMed2004

Versatile gene-specific sequence tags for Arabidopsis functional genomics: transcript profiling and reverse genetics applications.

Microarray transcript profiling and RNA interference are two new technologies crucial for large-scale gene function studies in multicellular eukaryotes. Both rely on sequence-specific hybridization between complementary nucleic acid strands, inciting us to create a collection of gene-specific sequence tags (GSTs) representing at least 21,500 Arabidopsis genes and which are compatible with both approaches. The GSTs were carefully selected to ensure that each of them shared no significant similarity with any other region in the Arabidopsis genome. They were synthesized by PCR amplification from genomic DNA. Spotted microarrays fabricated from the GSTs show good dynamic range, specificity, and sensitivity in transcript profiling experiments. The GSTs have also been transferred to bacterial plasmid vectors via recombinational cloning protocols. These cloned GSTs constitute the ideal starting point for a variety of functional approaches, including reverse genetics. We have subcloned GSTs on a large scale into vectors designed for gene silencing in plant cells. We show that in planta expression of GST hairpin RNA results in the expected phenotypes in silenced Arabidopsis lines. These versatile GST resources provide novel and powerful tools for functional genomics.

Arabidopsis↗