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Specific residues at every third position of siRNA shape its efficient RNAi activity.

Katoh T, Suzuki T - Nucleic Acids Res. (2007)

Bottom Line: Different efficacy of each siRNA is considered to result from sequence preference by protein components in RNAi.Since there was an obvious correlation between siRNA activity and its binding affinity to TRBP, a partner protein of human Dicer, the 3-nt periodicity might correlate with the affinity to TRBP.As an algorithm ('siExplorer') developed by this observation successfully calculated the activities of siRNAs targeting endogenous human genes, the 3-nt periodicity provides a new aspect unveiling siRNA functionality.

View Article: PubMed Central - PubMed

Affiliation: Department of Chemistry and Biotechnology, Graduate School of Engineering, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan.

ABSTRACT
Small interfering RNA (siRNA) induces sequence-specific post-transcriptional gene silencing in mammalian cells. Different efficacy of each siRNA is considered to result from sequence preference by protein components in RNAi. To obtain mechanistic insight into siRNA functionality, here we describe a complete data set of siRNA activities targeting all possible position of a single mRNA in human cells. Seven hundred and two siRNAs covering open reading frame of enhanced green fluorescent protein mRNA ( 720 bases) were examined with minimized error factors. The most important finding is that specific residues at every third position of siRNAs greatly influence its RNAi activity; the optimized base composition at positions 3n + 1 (4,7,10,13,16,19) in siRNAs have positive effects on the activity, which can explain the waving siRNA activity with 3 nucleotides (nt) periodicity in the sequential positions of mRNAs. Since there was an obvious correlation between siRNA activity and its binding affinity to TRBP, a partner protein of human Dicer, the 3-nt periodicity might correlate with the affinity to TRBP. As an algorithm ('siExplorer') developed by this observation successfully calculated the activities of siRNAs targeting endogenous human genes, the 3-nt periodicity provides a new aspect unveiling siRNA functionality.

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Comparison of the sequential knockdown activities of the 702 siRNAs targeting EGFP with the prediction values. (A) Correlation between siRNA activities and the B values (macro effect). siRNA activities (%), which are the rate of EGFP fluorescence reduction, are shown by bars. The B values for 702 siRNAs are plotted in blue. The correlation coefficient of the RNAi activity against the B values is 0.601 (P = 2.6 × 10−70). (B) The prediction values calculated by the algorithm are plotted in red. The correlation coefficient of the RNAi activities against the prediction values is 0.726 (P = 5.9 × 10−116). (C) Predicting periodical fluctuation of sequential siRNA activities. The nucleotide sequences show the passenger strand of EGFP siRNAs for positions 1–50. The colored bases represent bases that have positive or negative effects on the activity according to the analysis shown in Figure 3B. The RNAi activities (%) of the siRNAs for EGFP are shown in bars. The B value and the prediction value calculated for each siRNA are plotted in blue and red, respectively. The correlation coefficient of the RNAi activities against the prediction values in this region is 0.805 (P = 1.9 × 10−12).
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Figure 5: Comparison of the sequential knockdown activities of the 702 siRNAs targeting EGFP with the prediction values. (A) Correlation between siRNA activities and the B values (macro effect). siRNA activities (%), which are the rate of EGFP fluorescence reduction, are shown by bars. The B values for 702 siRNAs are plotted in blue. The correlation coefficient of the RNAi activity against the B values is 0.601 (P = 2.6 × 10−70). (B) The prediction values calculated by the algorithm are plotted in red. The correlation coefficient of the RNAi activities against the prediction values is 0.726 (P = 5.9 × 10−116). (C) Predicting periodical fluctuation of sequential siRNA activities. The nucleotide sequences show the passenger strand of EGFP siRNAs for positions 1–50. The colored bases represent bases that have positive or negative effects on the activity according to the analysis shown in Figure 3B. The RNAi activities (%) of the siRNAs for EGFP are shown in bars. The B value and the prediction value calculated for each siRNA are plotted in blue and red, respectively. The correlation coefficient of the RNAi activities against the prediction values in this region is 0.805 (P = 1.9 × 10−12).

Mentions: As shown in Figure 5C, the RNAi activities of siRNAs targeting sequential positions (1–50) in EGFP mRNA clearly showed periodical fluctuation at every third position. This phenomenon can be explained by the periodic efficacy of every third position in siRNAs. The 3-nt periodicity of waving RNAi activities is well observed in mRNA regions where A and U frequently appear at every third position, such as in positions 1–50, 110–160, 270–300 and 450–550 (Table S1). This periodical effect of every third position of siRNA implies the molecular mechanism of siRNA functionality in RNAi pathway.Figure 5.


Specific residues at every third position of siRNA shape its efficient RNAi activity.

Katoh T, Suzuki T - Nucleic Acids Res. (2007)

Comparison of the sequential knockdown activities of the 702 siRNAs targeting EGFP with the prediction values. (A) Correlation between siRNA activities and the B values (macro effect). siRNA activities (%), which are the rate of EGFP fluorescence reduction, are shown by bars. The B values for 702 siRNAs are plotted in blue. The correlation coefficient of the RNAi activity against the B values is 0.601 (P = 2.6 × 10−70). (B) The prediction values calculated by the algorithm are plotted in red. The correlation coefficient of the RNAi activities against the prediction values is 0.726 (P = 5.9 × 10−116). (C) Predicting periodical fluctuation of sequential siRNA activities. The nucleotide sequences show the passenger strand of EGFP siRNAs for positions 1–50. The colored bases represent bases that have positive or negative effects on the activity according to the analysis shown in Figure 3B. The RNAi activities (%) of the siRNAs for EGFP are shown in bars. The B value and the prediction value calculated for each siRNA are plotted in blue and red, respectively. The correlation coefficient of the RNAi activities against the prediction values in this region is 0.805 (P = 1.9 × 10−12).
© Copyright Policy - openaccess
Related In: Results  -  Collection

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getmorefigures.php?uid=PMC1851635&req=5

Figure 5: Comparison of the sequential knockdown activities of the 702 siRNAs targeting EGFP with the prediction values. (A) Correlation between siRNA activities and the B values (macro effect). siRNA activities (%), which are the rate of EGFP fluorescence reduction, are shown by bars. The B values for 702 siRNAs are plotted in blue. The correlation coefficient of the RNAi activity against the B values is 0.601 (P = 2.6 × 10−70). (B) The prediction values calculated by the algorithm are plotted in red. The correlation coefficient of the RNAi activities against the prediction values is 0.726 (P = 5.9 × 10−116). (C) Predicting periodical fluctuation of sequential siRNA activities. The nucleotide sequences show the passenger strand of EGFP siRNAs for positions 1–50. The colored bases represent bases that have positive or negative effects on the activity according to the analysis shown in Figure 3B. The RNAi activities (%) of the siRNAs for EGFP are shown in bars. The B value and the prediction value calculated for each siRNA are plotted in blue and red, respectively. The correlation coefficient of the RNAi activities against the prediction values in this region is 0.805 (P = 1.9 × 10−12).
Mentions: As shown in Figure 5C, the RNAi activities of siRNAs targeting sequential positions (1–50) in EGFP mRNA clearly showed periodical fluctuation at every third position. This phenomenon can be explained by the periodic efficacy of every third position in siRNAs. The 3-nt periodicity of waving RNAi activities is well observed in mRNA regions where A and U frequently appear at every third position, such as in positions 1–50, 110–160, 270–300 and 450–550 (Table S1). This periodical effect of every third position of siRNA implies the molecular mechanism of siRNA functionality in RNAi pathway.Figure 5.

Bottom Line: Different efficacy of each siRNA is considered to result from sequence preference by protein components in RNAi.Since there was an obvious correlation between siRNA activity and its binding affinity to TRBP, a partner protein of human Dicer, the 3-nt periodicity might correlate with the affinity to TRBP.As an algorithm ('siExplorer') developed by this observation successfully calculated the activities of siRNAs targeting endogenous human genes, the 3-nt periodicity provides a new aspect unveiling siRNA functionality.

View Article: PubMed Central - PubMed

Affiliation: Department of Chemistry and Biotechnology, Graduate School of Engineering, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan.

ABSTRACT
Small interfering RNA (siRNA) induces sequence-specific post-transcriptional gene silencing in mammalian cells. Different efficacy of each siRNA is considered to result from sequence preference by protein components in RNAi. To obtain mechanistic insight into siRNA functionality, here we describe a complete data set of siRNA activities targeting all possible position of a single mRNA in human cells. Seven hundred and two siRNAs covering open reading frame of enhanced green fluorescent protein mRNA ( 720 bases) were examined with minimized error factors. The most important finding is that specific residues at every third position of siRNAs greatly influence its RNAi activity; the optimized base composition at positions 3n + 1 (4,7,10,13,16,19) in siRNAs have positive effects on the activity, which can explain the waving siRNA activity with 3 nucleotides (nt) periodicity in the sequential positions of mRNAs. Since there was an obvious correlation between siRNA activity and its binding affinity to TRBP, a partner protein of human Dicer, the 3-nt periodicity might correlate with the affinity to TRBP. As an algorithm ('siExplorer') developed by this observation successfully calculated the activities of siRNAs targeting endogenous human genes, the 3-nt periodicity provides a new aspect unveiling siRNA functionality.

Show MeSH
Related in: MedlinePlus