Genetic Algorithm Approach for the Center Sequence Problem Arising in Post-transcriptional Gene Silencing

A fundamental aspect of Post-transcriptional gene silencing (PTGS) is the requirement of homology between the transgene sequence and the virus or mRNA sequence being silenced. For example, virus-resistant plants are resistant only to viruses that are very closely related to the virus from which the transgene was derived. One idea is to devise an artificial sequence that is at least 90 – 95% homologous to all virus genes. This requires an algorithm which can determine an artificial sequence with an optimal homology (or at least a 90 – 95% homology) to all of the virus sequences. The genetic algorithm presented in this paper serves this purpose. It should be of great value to all researchers who utilize PTGS, gene quelling, or RNAi. Mathematically, the task is to find the radius of a code S ⊂ {A,C,G, T }n. Experimental results suggest that this NPcomplete optimization problem can be approached well with a custom-built genetic algorithm (GA). Alternative approaches (exhaustive search, branch and bound, heuristics) are discussed and put in contrast to the GA approach.