Research Papers:

siRNAs with decreased off-target effect facilitate the identification of essential genes in cancer cells

Chunyan Li, Zhenzhen Liu, Fang Yang, Wensheng Liu, Di Wang, Encheng Dong, Yu Wang, Chung-I Wu and Xuemei Lu _

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Oncotarget. 2015; 6:21603-21613. https://doi.org/10.18632/oncotarget.4269

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Chunyan Li1,*, Zhenzhen Liu1,2,*, Fang Yang1,*, Wensheng Liu1, Di Wang1, Encheng Dong1, Yu Wang1, Chung-I Wu1 and Xuemei Lu1

1 CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Chaoyang District, Beijing, P. R. China

University of Chinese Academy of Sciences, Shijingshan District, Beijing, P. R. China

* These authors have contributed equally to this work

Correspondence to:

Xuemei Lu, email:

Keywords: essential gene, siRNA, off-target, cell viability, transcriptome

Received: February 12, 2015 Accepted: May 13, 2015 Published: May 25, 2015


Since the essential genes are crucial to the proliferation and survival of cancer cells, the interference of these genes is promising to be an option for cancer therapy to overcome heterogeneity. However, the essential genes are highly overestimated by RNA interference (RNAi) screenings, which is mainly caused by the pervasive off-target effect of small interference RNA (siRNA) and short hairpin RNA (shRNA). In the present study, we designed Match-Mismatch paired siRNAs to discriminate the on-target effect from off-target effect of siRNAs on cell viability. Only one of the 7 potential essential genes was validated as essential to cell viability, which demonstrates the high false positive rate in RNAi screenings. We modified the siRNA by introducing random nucleotides (N) into the guide strand to mitigate the off-target effect, without significantly compromising the on-target effect. The whole transcriptome profile analysis of cells transfected with siRNAs with or without Nindicates that siRNA-dN (with Ns on both the 2nd and the 18th bases of the guide strand) weakens the off-target effect by decreasing the unintended targets. The optimized siRNAs can be applied in the characterization of essential genes in cancer cells.

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