Affiliations: Department of Signal Processing, Tampere University of
Technology, Tampere, Finland | Department of Information and Computer Science,
Helsinki University of Technology, Helsinki, Finland
Note: [] Corresponding author: Kirsti Laurila, Department of Signal
Processing, Tampere University of Technology, P.O. Box 527, FI-33101 Tampere,
Finland. E-mail: kirsti.laurila@tut.fi
Abstract: Detailed knowledge of the mechanisms of transcriptional regulation
is essential in understanding the gene expression in its entirety.
Transcription is regulated, among other things, by transcription factors that
bind to DNA and can enhance or repress the transcription process. If a
transcription factor fails to bind to DNA or binds to a wrong DNA region that
can cause severe effects to the gene expression, to the cell and even to the
individual. The problems in transcription factor binding can be caused by
alterations in DNA structure which often occurs when parts of the DNA strands
are mutated. An increasing number of the identified disease-related mutations
occur in gene regulatory sequences. These regulatory mutations can disrupt
transcription factor binding sites or create new ones. We have studied effects
of mutations on transcription factor binding affinity computationally. We have
compared our results with experimentally verified cases where a mutation in a
gene regulatory region either creates a new transcription factor binding site
or deletes a previously existing one. We have investigated the statistical
properties of the changes on transcription factor binding affinity according to
the mutation type. Our analysis shows that the probability of a loss of a
transcription factor binding site and a creation of a new one varies remarkably
by the mutation type. Our results demonstrate that computational analysis
provides valuable information about the effect of mutations on transcription
factor binding sites. The analysis results also give a useful test set for
in vitro studies of regulatory mutation effects.
