Uwe Radelof

Automated image analysis for array hybridization experiments

MOTIVATION Image analysis is a major part of data evaluation for array hybridization experiments in molecular biology. The program presented here is designed to analyze automatically images from hybridization experiments with various arrangements: different kinds of probes (oligonucleotides or complex probes), different supports (nylon filters or glass slides), different labeling of probes (radioactively or fluorescently). The program is currently applied to oligonucleotide fingerprinting projects and complex hybridizations. The only precondition for the use of the program is that the targets are arrayed in a grid, which can be approximately transformed to an orthogonal equidistant grid by a projective mapping. RESULTS We demonstrate that our program can cope with the following problems: global distortion of the grid, missing of grid nodes, local deviation of the spot from its specified grid position. This is checked by different quality measures. The image analysis of oligonucleotide fingerprint experiments on an entire genetic library is used, in clustering procedures, to group related clones together. The results show that the program yields automatically generated high quality input data for follow up analysis such as clustering procedures. AVAILABILITY The executable files will be available upon request for academics.

RAI1 is a novel polyglutamine encoding gene that is deleted in Smith–Magenis syndrome patients

The human chromosomal band 17p11.2 is a genetically unstable interval. It has been shown to be deleted in patients suffering from Smith-Magenis syndrome. Previous efforts of physical and transcriptional mapping in 17p11.2 and subsequent genomic sequencing of the candidate interval allowed the identification of new genes that might be responsible for the Smith-Magenis syndrome. In this report, one of these genes named RAI1, the human homologue of the mouse Rai1 gene, has been investigated for its contribution to the syndrome. Expression analysis on different human adult and fetal tissues has shown the existence of at least three splice variants. Moreover, the most interesting feature of the gene is the presence of a polymorphic CAG repeat coding for a polyglutamine stretch in the amino terminal domain of the protein.

Xdigitise: visualization of hybridization experiments

UNLABELLED Xdigitise is a software system for visualization of hybridization experiments giving the user facilities to analyze the corresponding images manually or automatically. Images of the high-density DNA arrays are displayed as well as the results of an external image analysis bundled with Xdigitise, e.g. the spot locations are marked and the duplicate correlations are shown by a color scale. AVAILABILITY Xdigitise can be downloaded from http://www.molgen.mpg.de/~xdigitise.

A data-analysis pipeline for large-scale gene expression analysis

In this article we describe a method for characterization of large cDNA clone libraries based on oligonucleotide fingerprints (OFPs). The main advantage of this technique lies in that, without sequencing, each clone is tagged in an almost unique way, which has a couple of interesting applications, e.g. clustering of clones that belong to the same gene or gene family followed by sequencing of representative clones for each cluster. Moreover, small clusters are likely to represent rarely expressed genes, which are difficult to find by common approaches. We will demonstrate that in the EST projects carried out in our lab the global redundancy is very low compared to similar projects described in the literature, and simultaneously the number of unknown (novel) genes detected using this method is very high. In addition OFPs can be used directly for data base mining, since the sequences of the oligos matching a specific clone is known Recent results are presented, which underline the potential of our method in finding novel genes or genes homologous to known data. We will also address future applications in gene expression profiling, and give an outline of the various bioinformatics tools, which have been developed so far and which are used for automated data processing and analysis.