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Nucleic Acids Res. 2018 Jul 6;46(12):5950-5966. doi: 10.1093/nar/gky437.

Specificity of RNAi, LNA and CRISPRi as loss-of-function methods in transcriptional analysis.

Author information

1
Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge CB2 0RE, UK.
2
Institute of Cancer Research, 237 Fulham Road London SW3 6JB, UK.
3
European Bioinformatics Institute, European Molecular Biology Laboratory (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK.
4
Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire CB10 1SA, UK.

Abstract

Loss-of-function (LOF) methods such as RNA interference (RNAi), antisense oligonucleotides or CRISPR-based genome editing provide unparalleled power for studying the biological function of genes of interest. However, a major concern is non-specific targeting, which involves depletion of transcripts other than those intended. Little work has been performed to characterize the off-target effects of these common LOF methods at the whole-transcriptome level. Here, we experimentally compared the non-specific activity of RNAi, antisense oligonucleotides and CRISPR interference (CRISPRi). All three methods yielded non-negligible off-target effects in gene expression, with CRISPRi also exhibiting strong clonal effects. As an illustrative example, we evaluated the performance of each method for determining the role of an uncharacterized long noncoding RNA (lncRNA). Several LOF methods successfully depleted the candidate lncRNA but yielded different sets of differentially expressed genes as well as a different cellular phenotype upon depletion. Similar discrepancies between methods were observed with a protein-coding gene (Ch-TOG/CKAP5) and another lncRNA (MALAT1). We suggest that the differences between methods arise due to method-specific off-target effects and provide guidelines for mitigating such effects in functional studies. Our recommendations provide a framework with which off-target effects can be managed to improve functional characterization of genes of interest.

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