Efficient RNA interference depends on global context of the target sequence: quantitative analysis of silencing efficiency using Eulerian graph representation of siRNA.

Several aspects of gene silencing by small interfering RNA duplexes (siRNA) influence the efficiency of the silencing. They can be divided into two categories, one covering the cell-specific factors and the other covering molecular factors of the RNA interference (RNAi). A prerequisite for sequence-based siRNA design is that hybridization thermodynamics is the dominant factor. Our assumption is that cell-specific parameters (cell line, degradation, cross-hybridization, target conformation, etc.) can be pooled into an average cellular factor. Our hypothesis is that the molecular basis of the positional dependence of siRNA-induced gene silencing is the uniqueness of context of a corresponding target sequence segment relative to all other such segments along the attacked RNA. We encode this context into descriptors derived from Eulerian graph representation of siRNAs and show that the descriptor based upon the contextual similarity and predicted thermodynamic stability correlates with the experimentally observed silencing efficiency of human lamin A/C gene. We further show that information encoded in this regression function is generalizable and can be used as a predictor of siRNA efficiency in unrelated genes (CD54 and PTEN). In summary, our method represents an evolution of siRNA design from the currently used algorithms which are only qualitative in nature.