Limits...
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.

Show MeSH

Related in: MedlinePlus

Effect of the total base composition of 702 siRNAs on their ability to silence EGFP expression. Correlation between the total base composition of the 702 EGFP siRNAs and their activities. The correlation coefficients are plotted against the different B values that were obtained by changing the coefficients for each base in Equation (1). (A) Coefficients for A + U = 0.75, G + C = 0.25. (B) Coefficients for A + U = 0.25, G + C = 0.75. Other graphs with different coefficients are shown in Figure S3A–S.
© Copyright Policy - openaccess
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC1851635&req=5

Figure 3: Effect of the total base composition of 702 siRNAs on their ability to silence EGFP expression. Correlation between the total base composition of the 702 EGFP siRNAs and their activities. The correlation coefficients are plotted against the different B values that were obtained by changing the coefficients for each base in Equation (1). (A) Coefficients for A + U = 0.75, G + C = 0.25. (B) Coefficients for A + U = 0.25, G + C = 0.75. Other graphs with different coefficients are shown in Figure S3A–S.

Mentions: To elucidate the other factors in siRNA sequence to be involved in its activity, we next examined base composition of each siRNA. The base composition of each siRNA was represented as the value B (base composition value), which was calculated by Equation (1) given below, where NX stands for the number of specific bases (X = A, U, G or C) in the siRNA and PX stands for the coefficient given to each base (X = A, U, G or C). Summation of NX and PX must be 19 and 1, respectively.1The correlation between the B values obtained with various PX values for each base and the RNAi activities of all the siRNAs were then analyzed to calculate R values. This analysis was completely carried out by examining all possible combination of PX values changing at 0.05 steps, showing the R values ranging from −0.601 to 0.601 (Figures 3A,B and S3A–S in supplementary information). To obtain a higher R value between the B value and the RNAi activity, we found that PA + PU has to be greater than PG + PC, PA has to be greater than PU, and PG has to be greater than PC (Figures 3A,B and S3A–S). The best coefficients to achieve the highest R factor (0.601) for each base was found to be PA:PU:PG:PC = 0.4:0.35:0.15:0.1 (Figure 3A). The worst coefficients to yield the lowest R factor (−0.601) was found to be PA:PU:PG:PC = 0.1:0.15:0.35:0.4 (Figure 3B). The results showed that the RNAi activity turned out to correlate closely with the total base composition of siRNA sequence.Figure 3.


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

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

Effect of the total base composition of 702 siRNAs on their ability to silence EGFP expression. Correlation between the total base composition of the 702 EGFP siRNAs and their activities. The correlation coefficients are plotted against the different B values that were obtained by changing the coefficients for each base in Equation (1). (A) Coefficients for A + U = 0.75, G + C = 0.25. (B) Coefficients for A + U = 0.25, G + C = 0.75. Other graphs with different coefficients are shown in Figure S3A–S.
© Copyright Policy - openaccess
Related In: Results  -  Collection

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

Figure 3: Effect of the total base composition of 702 siRNAs on their ability to silence EGFP expression. Correlation between the total base composition of the 702 EGFP siRNAs and their activities. The correlation coefficients are plotted against the different B values that were obtained by changing the coefficients for each base in Equation (1). (A) Coefficients for A + U = 0.75, G + C = 0.25. (B) Coefficients for A + U = 0.25, G + C = 0.75. Other graphs with different coefficients are shown in Figure S3A–S.
Mentions: To elucidate the other factors in siRNA sequence to be involved in its activity, we next examined base composition of each siRNA. The base composition of each siRNA was represented as the value B (base composition value), which was calculated by Equation (1) given below, where NX stands for the number of specific bases (X = A, U, G or C) in the siRNA and PX stands for the coefficient given to each base (X = A, U, G or C). Summation of NX and PX must be 19 and 1, respectively.1The correlation between the B values obtained with various PX values for each base and the RNAi activities of all the siRNAs were then analyzed to calculate R values. This analysis was completely carried out by examining all possible combination of PX values changing at 0.05 steps, showing the R values ranging from −0.601 to 0.601 (Figures 3A,B and S3A–S in supplementary information). To obtain a higher R value between the B value and the RNAi activity, we found that PA + PU has to be greater than PG + PC, PA has to be greater than PU, and PG has to be greater than PC (Figures 3A,B and S3A–S). The best coefficients to achieve the highest R factor (0.601) for each base was found to be PA:PU:PG:PC = 0.4:0.35:0.15:0.1 (Figure 3A). The worst coefficients to yield the lowest R factor (−0.601) was found to be PA:PU:PG:PC = 0.1:0.15:0.35:0.4 (Figure 3B). The results showed that the RNAi activity turned out to correlate closely with the total base composition of siRNA sequence.Figure 3.

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