Understanding the regulation of gene expression requires the identification of cis -acting control elements that modulate gene function. The recent availability of complete genome sequences and profiles of mRNA expression has facilitated the development and utilization of computational methods to identify discrete regulatory elements. We have developed an oligomer counting method that identifies sequences that occur significantly more often in a group of interest relative to other genes in the genome. The use of a second parameter, which measures the frequency of oligomers within the group of interest, allows the detection of false positive signals caused by very infrequent oligomers that would otherwise appear as significant. Applying this method to gene groups that have a common expression pattern or shared function should identify oligomers that comprise cis -acting control elements. As a test of this method, we applied this approach to a set of intron-containing yeast genes, where we easily identified the known splicing signals as control elements. We have used this training set to examine how this method is affected by the length of the oligomer examined, as well as the size and composition of the gene group. These simulations allowed us to identify rules for selecting groups of genes to analyze. Finally, application of this method to nuclear genes encoding proteins targeted to the mitochondria identified a new putative cis -acting sequence in the 3'-untranslated region of this family of genes, which may play a role in mRNA localization or the regulation of mRNA stability or translation.

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Journal Article | Research Support, U.S. Gov't, P.H.S.

Authors

Jacobs Anderson JS, Parker R

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