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The potentiation and subsequent initiation of transcription are complex biological phenomena. The region of attachment of the chromatin fiber to the nuclear matrix, known as the matrix attachment region or scaffold attachment region (MAR or SAR), are thought to be requisite for the transcriptional regulation of the eukaryotic genome. As expressed sequences should be contained in these regions, it becomes significant to answer the following question: can these regions be identified from the primary sequence data alone and subsequently used as markers for expressed sequences? This paper represents an effort toward achieving this goal and describes a mathematical model for the detection of MARs. The location of matrix associated regions has been linked to a variety of sequence patterns. Consequently, a list of these patterns is compiled and represented as a set of decision rules using an AND-OR formulation. The DNA sequence was then searched for the presence of these patterns and a statistical significance was associated with the frequency of occurrence of the various patterns. Subsequently, a mathematical potential value,MAR-Potential, was assigned to a sequence region as the inverse proportion to the probability that the observed pattern population occurred at random. Such a MAR detection process was applied to the analysis of a variety of known MAR containing sequences. Regions of matrix association predicted by the software essentially correspond to those determined experimentally. The human T-cell receptor and the DNA sequence from the Drosophila bithorax region were also analyzed. This demonstrates the usefulness of the approach described as a means to direct experimental resources.

Mathematical model to predict regions of chromatin attachment to the nuclear matrix