Affiliations: Department of Computer Science, Ben-Gurion University,
Beer-Sheva 84105, Israel | Department of Life Sciences, Ben-Gurion University,
Beer-Sheva 84105, Israel | Department of Plant Sciences, Weizmann Institute of
Science, Rehovot 76100, Israel
Abstract: Three-way junctions in folded RNAs have been investigated both
experimentally and computationally. The interest in their analysis stems from
the fact that they have significantly been found to possess a functional role.
In recent work, three-way junctions have been categorized into families
depending on the relative lengths of the segments linking the three helices.
Here, based on ideas originating from computational geometry, an algorithm is
proposed for detecting three-way junctions in data sets of genes that are
related to a metabolic pathway of interest. In its current implementation, the
algorithm relies on a moving window that performs energy minimization folding
predictions, and is demonstrated on a set of genes that are involved in purine
metabolism in plants. The pattern matching algorithm can be extended to other
organisms and other metabolic cycles of interest in which three-way junctions
have been or will be discovered to play an important role. In the test case
presented here with, the computational prediction of a three-way junction in
Arabidopsis that was speculated to have an interesting functional role is
verified experimentally.
Keywords: Three-way junctions, folding prediction by energy minimization
