METHOD

siRNA-mediated gene silencing

About authors

1 Laboratory of Functional Genomics,
Research Centre of Medical Genetics, Moscow, Russia

2 Laboratory of Medical and Genetic Technologies, Department of Basic Research of Research Institute for Medicine and Dentistry,
Yevdokimov Moscow State University of Medicine and Dentistry, Moscow, Russia

3 Genomic Functional Analysis Laboratory,
Moscow Institute of Physics and Technology (State University), Dolgoprudny, Russia

Correspondence should be addressed: Mikhail Skoblov
ul. Moskvorechie, d. 1, Moscow, Russia, 115478; moc.liamg@volboksm

About paper

Contribution of the authors to this work: Vyakhirava JV — analysis of literature, research planning, data collection, analysis and interpretation, drafting of a manuscript; Filatova AYu — analysis of literature, data collection, analysis and interpretation, drafting of a manuscript; Krivosheeva IA — analysis of literature, data collection, analysis and interpretation, drafting of a manuscript; Skoblov MYu — drafting of a manuscript. All authors participated in editing of the manuscript.

Received: 2017-06-25 Accepted: 2017-06-28 Published online: 2017-07-19
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Fig. 1. Knockdown experiment: the plan
Fig. 2. Predicted ΔΔCt detectable by real-time PCR. Prediction is based on different transfection and knockdown efficiencies
Fig. 3. Electrophoresis of high quality RNA extracts obtained from the lysate. 1 — the 28S rRNA band, 2 — the 18SrRNA band
Fig. 4. A bar chart representing real-time PCR data
Fig. 5. The results of the МТТ-assay following HOXA7 knockdown (Tang et al. [55])
Table 1. Rules for nucleotides in siRNA sequence. AS is the antisense strand, S is the sense strand. Grey cells represent positions of siRNA nucleotides (Lagana et al., [26])
Table 2. The most popular software tools used for siRNA design
Table 3. Optimizing transfection for a 96-well plate
Table 4. Calculating the amount of siRNA and Metafectene for different plate types per transfection
Table 5. The reaction mix for reverse transcription