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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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Related in: MedlinePlus

Scatter plots for the knockdown activities of the 702 EGFP siRNAs versus thermodynamic stability of both ends in siRNAs. (A) Scatter plot for the activities of 702 siRNAs versus thermodynamic energy of the guide strand 5′ end. The correlation coefficient (R) is 0.444 (P = 2.6 × 10−35). (B) Scatter plot for the activities of 702 siRNAs versus thermodynamic energy of the passenger strand 5′ end. The correlation coefficient (R) is 0.135 (P = 3.4 × 10−4). (C) Scatter plot for the activities of 702 siRNAs versus stability difference (g.s. − p.s.) of both strands. The correlation coefficient (R) is 0.236 (P = 2.4 × 10−10). Blue spots represent 10 siRNAs that exhibit less stable guide strand 5′ end but show lower activity (less than 30). Red spots represent 10 siRNAs that exhibit more stable guide strand 5′ end but show higher activity (more than 70). Number near the spot corresponds to the passenger strand 5′ end position of each siRNA in EGFP mRNA.
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Figure 2: Scatter plots for the knockdown activities of the 702 EGFP siRNAs versus thermodynamic stability of both ends in siRNAs. (A) Scatter plot for the activities of 702 siRNAs versus thermodynamic energy of the guide strand 5′ end. The correlation coefficient (R) is 0.444 (P = 2.6 × 10−35). (B) Scatter plot for the activities of 702 siRNAs versus thermodynamic energy of the passenger strand 5′ end. The correlation coefficient (R) is 0.135 (P = 3.4 × 10−4). (C) Scatter plot for the activities of 702 siRNAs versus stability difference (g.s. − p.s.) of both strands. The correlation coefficient (R) is 0.236 (P = 2.4 × 10−10). Blue spots represent 10 siRNAs that exhibit less stable guide strand 5′ end but show lower activity (less than 30). Red spots represent 10 siRNAs that exhibit more stable guide strand 5′ end but show higher activity (more than 70). Number near the spot corresponds to the passenger strand 5′ end position of each siRNA in EGFP mRNA.

Mentions: It is known that Drosophila Dicer-2 with its partner protein recognizes siRNA asymmetrically by sensing relative thermodynamic instability at the 5′ ends of both strands. This asymmetric recognition is supposed to be the fundamental principle of the strand selection for siRNAs (31,32). To investigate whether the complete set of siRNA activities in this study actually correlate with the instability of the guide strand 5′ end, we calculated thermodynamic energy of both 5′ ends for 702 siRNAs (see Materials and Methods and Table S1). The thermodynamic stability of the guide or passenger strand 5′ end for each siRNA is plotted with its RNAi activity (Figures 2A,B). As expected, there is an apparent correlation between instability of the guide strand 5′ end and its RNAi activity with a correlation coefficient (R value) 0.444 (P = 2.6 × 10−35) (Figure 2A). Meanwhile, as shown in Figure 2B, there is little correlation between the instability of passenger strand 5′ end and its RNAi activity (R value is 0.135, P = 3.4 × 10−4). If human Dicer with its partner (TRBP) senses the stability of the passenger strand 5′ end in a positive manner, the correlation coefficient should be a negative value in this plot. In addition, to examine relative stability of both strands, we made another plot (Figure 2C) for the RNAi activity against the energy difference for each siRNA which was calculated by the differential energy of the guide and the passenger strand 5′ ends (Table S1). Although it is a positive correlation, the plots are still dispersed in the graph with R factor 0.236 (P = 2.4 × 10−10). These results clearly illustrated that the instability of the guide strand 5′ end is a major factor contributing to the asymmetrical strand selection.Figure 2.


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

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

Scatter plots for the knockdown activities of the 702 EGFP siRNAs versus thermodynamic stability of both ends in siRNAs. (A) Scatter plot for the activities of 702 siRNAs versus thermodynamic energy of the guide strand 5′ end. The correlation coefficient (R) is 0.444 (P = 2.6 × 10−35). (B) Scatter plot for the activities of 702 siRNAs versus thermodynamic energy of the passenger strand 5′ end. The correlation coefficient (R) is 0.135 (P = 3.4 × 10−4). (C) Scatter plot for the activities of 702 siRNAs versus stability difference (g.s. − p.s.) of both strands. The correlation coefficient (R) is 0.236 (P = 2.4 × 10−10). Blue spots represent 10 siRNAs that exhibit less stable guide strand 5′ end but show lower activity (less than 30). Red spots represent 10 siRNAs that exhibit more stable guide strand 5′ end but show higher activity (more than 70). Number near the spot corresponds to the passenger strand 5′ end position of each siRNA in EGFP mRNA.
© Copyright Policy - openaccess
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC1851635&req=5

Figure 2: Scatter plots for the knockdown activities of the 702 EGFP siRNAs versus thermodynamic stability of both ends in siRNAs. (A) Scatter plot for the activities of 702 siRNAs versus thermodynamic energy of the guide strand 5′ end. The correlation coefficient (R) is 0.444 (P = 2.6 × 10−35). (B) Scatter plot for the activities of 702 siRNAs versus thermodynamic energy of the passenger strand 5′ end. The correlation coefficient (R) is 0.135 (P = 3.4 × 10−4). (C) Scatter plot for the activities of 702 siRNAs versus stability difference (g.s. − p.s.) of both strands. The correlation coefficient (R) is 0.236 (P = 2.4 × 10−10). Blue spots represent 10 siRNAs that exhibit less stable guide strand 5′ end but show lower activity (less than 30). Red spots represent 10 siRNAs that exhibit more stable guide strand 5′ end but show higher activity (more than 70). Number near the spot corresponds to the passenger strand 5′ end position of each siRNA in EGFP mRNA.
Mentions: It is known that Drosophila Dicer-2 with its partner protein recognizes siRNA asymmetrically by sensing relative thermodynamic instability at the 5′ ends of both strands. This asymmetric recognition is supposed to be the fundamental principle of the strand selection for siRNAs (31,32). To investigate whether the complete set of siRNA activities in this study actually correlate with the instability of the guide strand 5′ end, we calculated thermodynamic energy of both 5′ ends for 702 siRNAs (see Materials and Methods and Table S1). The thermodynamic stability of the guide or passenger strand 5′ end for each siRNA is plotted with its RNAi activity (Figures 2A,B). As expected, there is an apparent correlation between instability of the guide strand 5′ end and its RNAi activity with a correlation coefficient (R value) 0.444 (P = 2.6 × 10−35) (Figure 2A). Meanwhile, as shown in Figure 2B, there is little correlation between the instability of passenger strand 5′ end and its RNAi activity (R value is 0.135, P = 3.4 × 10−4). If human Dicer with its partner (TRBP) senses the stability of the passenger strand 5′ end in a positive manner, the correlation coefficient should be a negative value in this plot. In addition, to examine relative stability of both strands, we made another plot (Figure 2C) for the RNAi activity against the energy difference for each siRNA which was calculated by the differential energy of the guide and the passenger strand 5′ ends (Table S1). Although it is a positive correlation, the plots are still dispersed in the graph with R factor 0.236 (P = 2.4 × 10−10). These results clearly illustrated that the instability of the guide strand 5′ end is a major factor contributing to the asymmetrical strand selection.Figure 2.

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