Title :
Maximum sequence alignment fails to predict off-targeted gene regulation by RNAi
Author :
Birmingham, Amanda ; Anderson, Emily M. ; Marshall, William S. ; Khvorova, Anastasia
Abstract :
We have employed various sequence alignment algorithms and scoring techniques to determine whether current computational tools accurately predict genes that will be off-targeted by the RNA interference (RNAi) pathway. Our studies show that distributions of maximum alignment scores for off-targeted and untargeted genes are statistically indistinguishable, indicating that maximum complementarity by itself is an unsatisfactory predictor of off-targeting. Interestingly, a highly significant association was observed between off-targeting and exact complementarity between the seed region (bases 2-7) of siRNA and their off-targeted genes. This pattern has been previously recognized in microRNA-mediated gene knockdown and suggests a distinctive role for the 5 terminus of these strands in RNAi-triggered gene suppression.
Keywords :
biology computing; genetics; macromolecules; organic compounds; pattern recognition; RNA; computational tools; gene regulation; gene suppression; microRNA-mediated gene knockdown; scoring techniques; sequence alignment; Bars; Bioinformatics; Conferences; Databases; Network address translation; Proteins; RNA; Software design; Strontium; Testing;
Conference_Titel :
Computational Systems Bioinformatics Conference, 2005. Workshops and Poster Abstracts. IEEE
Print_ISBN :
0-7695-2442-7
DOI :
10.1109/CSBW.2005.90