In Silico Prediction of Matrix Attachment Regions in Large Genomic Sequences

Thomas Werner
Genomatix Software
Karlstr. 55
D-80333 München
telephone: +49-89-5490839-0
fax: +49-89-5490839-9
prestype: Platform
presenter: Dr. Thomas Werner

Matthias Frisch1, Kornelie Frech1, Andreas Klingenhoff1, Kerstin Quandt1, Ines Liebich2,
and Thomas Werner1,3

1Genomatix Software GmbH, Karlstr. 55, D-80333 München, Germany.
2 Research Group Bioinformatics, Gesellschaft für Biotechnologische Forschung mbH, Mascheroder Weg 1, D-38124 Braunschweig, Germany.
3 Institute of Experimental Genetics, GSF-National Research Center for Environment and Health, Ingolstädter Landstrasse 1, D-85764 Neuherberg, Germany.

Matrix attachment regions (MARs) are essential regulatory DNA elements of eukaryotic cells. They are major determinants of locus control of expression and shield gene expression from position effects. Experimental detection of MARs requires substantial efforts not suitable for large-scale screening of genomic sequences. In silico prediction of MARs can provide a crucial first selection step to reduce the amount of candidates. We used 34 experimentally defined MARs as training set and generated a library of 97 MAR-associated, AT-rich patterns described as weight matrices. We developed a new tool, SMARTest, identifying potential MARs in genomic sequences. SMARTest carries out a density analysis based on the MAR matrix library. The SMARTest approach does not depend on the sequence context and is suitable to analyse long genomic sequences up to the size of whole chromosomes on a workstation. To demonstrate the feasibility of large-scale MAR prediction we analysed the recently published chromosome 22 sequence and found 1198 MAR candidates.

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