Chapter Analysis of the Dynamics of Co-transcriptional Binding Accessibility of AON Target Sites In this chapter, dynamics of the co-transcriptional binding accessibility of previously published AON target sites are analyzed, and correlated with the degree of reported efficiency in the induction of exon skipping 7.1 Overview of the analysis methodology The analysis carried out in this chapter involves the following sequential steps: Data collection (Section 7.2) Previously published AONs whose efficiency in the induction of selective exon skipping in the dystrophin pre-mRNA has been tested in wet experiments are gathered; only AONs that target ESE sites are included They are then graded according to their reported efficiencies Prediction of the co-transcriptional secondary structures of exons (Section 7.3) A model to approximate transcription is used to predict the co-transcriptional secondary structures of exons, which are targeted by the AONs gathered in step Analysis of the dynamics of the co-transcriptional binding accessibility (Sections 7.4 and 7.5) The co-transcriptional binding accessibility of each nucleotide within an AON target site is determined based on whether it is paired in the predicted co-transcriptional secondary structures obtained in step Several 131 novel scoring systems are formulated to quantify the dynamics of the cotranscriptional binding accessibility Test for correlation between reported AON efficiencies in inducing exon skipping with their co-transcriptional binding accessibility (Sections 7.4 and 7.5) The scores (formulated in step 3) in each grade of AONs are tested for statistical differences and significances against other grades using two-sample KolmogorovSmirnov (K-S) test; each grade of AONs has distinct reported efficiencies All statistical tests are performed using the statistical software, R Version 2.0.0 (http://www.R-project.org) Note: throughout the thesis, “efficacy” is used to describe qualitatively the ability of an AON to induce selective exon skipping whereas “efficiency” is used to quantify the percentage of total mRNA molecules whose selected exon is skipped by an AON 7.2 Data set for analysis A total of 176 AONs, reported by two independent sources Aartsma-Rus et al (2005) and Wilton et al (2007), that target ESEs to induce the skipping of 67 exons in dystrophin pre-mRNA was analyzed Although the cell lines and experimental protocols used in these two studies were similar, the AONs from each study were analyzed separately because of the following reasons The range of AON lengths, which may influence AON performance (Harding et al., 2007), differed significantly between the studies The AONs from the two sources Aartsma-Rus et al (2005) and Wilton et al (2007) showed median lengths of 19 and 26 nucleotides respectively, and for the purpose of this study, are henceforth denoted as Set A and Set B 132 respectively Note that only 62 out of the 82 AONs reported by Wilton et al (2007) are included in Set B, as the remaining ones either target non-ESE sites or result in unspecific exon skipping Secondly, as breakdown in Table 7-1, the respective sources graded their AONs differently according to their efficiencies in inducing exon skipping; AON efficiency was calculated based on densitograph semi-quantification in the two publications Table 7-1 Classification of published AON (antisense oligonucleotides) sequences Published AONs from two independent sources are denoted as Set A and B respectively In each set, AONs are classified into different grades according to their efficiencies (E) in the induction of exon skipping Set A Number of AONs Set B Number of AONs Grade (++) E ≥ 25% 41 Grade (++) E ≥ 30% 35 7.3 Prediction of Grade (+) 0% < E < 25% 35 Grade (+ 1) 10% ≤ E < 30% 11 Grade (–) E = 0% 38 Grade (+ 2) 0% < E < 10% co-transcriptional Total 114 Grade (–) E = 0% Total 62 secondary structures of exons The co-transcriptional secondary structures of exons are requisite to determine the co-transcriptional binding accessibility of each AON target site Computational tools are used to predict these secondary structures, as current experimental means to determine them is unavailable While computer algorithms that consider the mRNA secondary structure folding paths during transcription are available (Isambert and Siggia, 2000; Gultyaev et al., 1995), computational time is tractable only for sequences up to 400 nucleotides, which is too short for the use in this study 133 Alternatively, algorithms that could efficiently predict a long fully synthesized mRNA are considered (Zuker, 2003; Knudsen and Hein, 2003; Ding and Lawrence, 2003; Flamm et al., 2000) Among them is mfold (Zuker, 2003), which is chosen in this study because firstly it has a relatively high average prediction accuracy of 70% (Mathews et al., 1999) and secondly, it has the advantage of being used in most published experimental work on AONs that target the dystrophin gene (Aartsma-Rus et al., 2002, 2005; Errington et al., 2003) and, therefore, results of this study can be compared with them on a common basis AON target site intron intron Direction of pre-mRNA elongation exon 1500 nt 1st step of transcriptional analysis 5’ 3’ 2nd step of transcriptional analysis 3rd step of transcriptional analysis nt Last step of transcriptional analysis Figure 7-1 A model to approximate transcription elongation To approximate the transcription elongation process, a “window of analysis” is shifted one nucleotide at a time along the pre-mRNA sequence towards the 3” end At the first window, its 3’ end coincides with the 3’ end of the target exon Correspondingly, at the last window, its 5’ end coincides with the 5’ end of the target exon Each window of analysis corresponds to a step of transcriptional analysis at which the possible secondary structures of its sequence were predicted 134 As mfold does not consider folding paths, they are approximated using the model depicted in Figure 7-1 A “window of analysis” of pre-determined sequence length of 1500 nucleotides that includes the full length of the targeted exon corresponds to a “step of transcriptional analysis” To approximate the transcription elongation process, the window of analysis is shifted one nucleotide at a time along the pre-mRNA sequence towards the 3’ end At each step of transcriptional analysis, the possible secondary structures for the window sequence are predicted using mfold version 3.1 (Zuker, 2003; Mathews et al., 1999) Since it is highly probable that the nascent pre-mRNA may not have the chance to assume optimal secondary structures, sub-optimal secondary structures whose energies lie within 5% of the optimum are considered On average, 44,582 secondary structures are predicted per exon of which 24 to 47 secondary structures are predicted in each step of transcriptional analysis; number of secondary structures predicted in the 79 exons is given in Appendix A-17 Note that the model considers only the local secondary structures around the target exon As abundant hnRNPs (heterogeneous nuclear ribonuclear proteins) package long introns into compact secondary structures that deterred long-distance or global intra-molecular complementary base pairings (Alberts et al., 2002), this assumption is justified given that long introns are typical in dystrophin gene (Figure 6-1 of Chapter 6) On the other hand, the 1500 nucleotides length of the window of analysis is estimated from experimental measurements It has been reported that the 3’ splice site is recognized 48 seconds after it is transcribed (Beyer and Osheim, 1988) Based on the measured elongation rate of dystrophin pre-mRNA at 1700 to 2500 nucleotides per minute (Tennyson et al., 1995), about 1360 to 2000 nucleotides would be appended to the nascent transcript during this period Nevertheless, co- 135 transcriptional secondary structures of exons (62 bp), 29 (150 bp) and 59 (269 bp) were also predicted with lengths of window of analysis of 1200 and 2000 nucleotides, but however, no statistical differences in their co-transcriptional secondary structures are detected (data not shown) 7.4 Analysis of the dynamics of co-transcriptional binding accessibility of AON target sites Four levels of analysis using scoring methodologies of increasing complexity are used to score the binding accessibility of AON target sites in the sets of published AONs Scores at each level of analysis were then correlated with the degree of reported AON efficiency and efficacy for each set of AONs Note that these scoring methodologies are applicable for any secondary structure prediction tools, as long as cotranscriptional secondary structures of AON target sites can be generated 7.4.1 First level analysis At this simplest level of analysis, the binding accessibility score of an AON target site (L1) is computed To so however, the binding accessibility score of each nucleotide within the AON target site is needed, and is determined by this ratio: Number of predicted secondary structures in which the nucleotide is unpaired Total number of secondary structures predicted 136 Note: all secondary structures predicted at every step of transcriptional analysis (Figure 7-1) are included in the calculation; a nucleotide is “unpaired” when it does not form complementary base pairing with another nucleotide within the pre-mRNA Thus, the accessibility score for the AON target site, L1 is: Sum of nucleotide accessibility scores for all nucleotides within the AON target site Total number of nucleotides in AON target site The L1 scores for each AON target site analyzed are tabulated in Appendix A18 Two-sample Kolmogorov-Smirnov (K-S) test is used to test for statistical differences and significances of the L1 scores for target sites between any two AON grades of the same set Table 7-2 tabulates the p-values for the statistical tests To ensure consistent test outcomes, two exclusive one-tailed tests, i.e., Ho: 1st < 2nd and Ho: 1st > 2nd (columns and 3) are performed for each test case (as described in column one) For instance, for the test case (++ versus –) of Set A, the null hypothesis, Ho: 1st < 2nd tests for whether L1 scores for target sites in (++) AONs are smaller than those in (–) AONs The null hypothesis is true and accepted if p-value < 0.05, or is rejected if otherwise Thus, the test outcomes in a particular test case are inconsistent if the null hypotheses of the two tests are both true 137 Table 7-2 p-values for K-S tests using the first level score (L1) p-values (columns and 3) of the K-S tests for the target sites of AONs in (A) Set A and (B) Set B Statistically significant p-values are indicated in bold and underlined Column describes the test case The last column indicates whether the particular test case tests for AON efficacy and/or efficiency In (B), (+ 1,2) denotes AONs merged from (+ 1) and (+ 2) AONs Note: Wilcoxon rank-sum test cannot be used as one of its key assumptions is violated, i.e., distributions of each AON grade’s L1 scores are distinct (box plots not shown) A Test case: 1st vs 2nd Ho : H o: 1st < 2nd 1st > 2nd 0.21 0.97 (++) vs (–) 0.41 0.94 (+) vs (–) 0.99 (++, +) vs (–) 0.42 0.44 0.57 (++) vs (+) 0.85 (++) vs (+, –) 0.21 Test for Efficacy Efficacy Efficacy Efficiency Both B Test case: 1st vs 2nd Ho : Ho : 1st < 2nd 1st > 2nd 0.032 (++) vs (–) 0.93 0.037 (+1, 2) vs (–) 0.023 (++, +1, 2) vs (–) 0.99 0.92 0.036 (+1) vs (–) 0.97 0.076 (+2) vs (–) 0.90 0.44 (++) vs (+1, 2) 0.90 0.55 (++) vs (+1) 0.68 0.45 (++) vs (+2) 0.61 0.82 (+1) vs (+2) 0.38 (++) vs (+1, 2, –) 0.96 Test for Efficacy Efficacy Efficacy Efficacy Efficacy Efficiency Efficiency Efficiency Efficiency Both For AONs in Set A, L1 scores for target sites in each grade of AONs not show any statistical difference (Table 7-2A), which agrees with the results reported by Aartsma-Rus et al (2005) and Harding et al (2007) For AONs in Set B, L1 scores for target sites of (++) and (+ 1) AONs are statistically higher that those of (–) AONs; their p-values are highlighted in Table 7-2B This result indicates that (++) and (+ 1) AON target sites are more accessible than (–) AON target sites, and therefore, the L1 score could correlate with AON efficacy for Set B AONs 7.4.2 Second level analysis At this level of analysis, the nucleotide accessibility scores of every nucleotide in an AON target site were screened to determine the presence of two or more scores with values below 0.1 occurring consecutively in the nucleotide sequence of the target site 138 (Figure 7-2) Such grouping of below 0.1 nucleotide accessibility scores is termed a “low accessibility cluster”; refer to Table S3 of Wee et al (2008a) (attached in Appendix A-1) for the list of low accessibility clusters manifested in all the analyzed AONs In Set A, 71% of target sites of (–) AONs had one or more low accessibility clusters While only 17% of target sites of (+) AONs had one or more clusters, they were manifested in 52% of target sites of (++) AONs Set B also exhibited similar trends: 71%, 70% and 80% of target sites of (–) AONs, (+) AONs and (++) AONs respectively had one or more clusters Therefore, the presence of these clusters in the AON target sites cannot correlate with AON efficacy and efficiency h43AON5 (++) h46AON4 (+) h48AON1 (–) 1 0.9 0.9 0.9 0.8 0.8 0.8 0.7 0.7 0.7 0.6 0.6 0.6 0.5 0.5 0.5 0.4 0.4 0.4 0.3 0.3 0.3 0.2 0.2 0.2 0.1 0.1 0 90 92 94 96 98 100 102 104 106 108 0.1 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 Figure 7-2 Nucleotide accessibility scores of all the nucleotide in three representative AON target sites are depicted In each plot, the horizontal axis represents the nucleotide position in the respective target exon and the nucleotide accessibility score is plotted on the vertical axis The low accessibility clusters are indicated in red 7.4.3 Third level analysis The nucleotide accessibility scores at the first and second levels of analysis are mean scores As a result, two nucleotides with identical accessibility scores may have markedly different numbers of unpaired predicted secondary structures at each step of transcriptional analysis In analyzing accessibility for AON binding, it may be 139 important to take into account steps of transcriptional analysis in which a nucleotide is predicted to have total absence of unpaired secondary structures, i.e the nucleotide is predicted to be completely inaccessible or “engaged” at the particular step of transcriptional analysis, as illustrated in Figure 7-3B For the purpose of analysis, at every step of transcriptional analysis, each nucleotide in the AON target site that is engaged may then be depicted in a plot as illustrated in Figure 7-4 Table S4 of Wee et al (2008a) (attached in Appendix A-1) tabulates these plots for all the AON target sites analyzed 140 In contrast to L1 score, the higher the L3 score, the less accessible a target site is for AON binding Appendix A-18 tabulates the L3 scores for all the AONs analyzed For Set A AONs, target sites of (++) AONs have statistically lower engaged scores than target sites of both (–) and (+) AONs (Table 7-3A) Therefore, L3 score can statistically differentiate both AON efficacy and efficiency However, seven outlier AONs (6% of total AONs) are identified In this context, these are AONs in which the target site L3 scores contradict their AON grades For instance, target sites of h52AON2 and h60AON2 graded as (─) could not induce exon skipping although their L3 scores are below the 5th-percentile of L3 scores of (++) AON target sites (Appendix A-18) On the other hand, target sites of h45AON5 and h46AON4 graded as (+) and target sites of h51AON29, h55AON5 and h77AON2 graded as (++) all have L3 scores higher than the 95th-percentile of L3 scores of (─) AON target sites (Appendix A-18) but could still induce exon skipping The omission of these outlier AONs strengthen the correlation of L3 scores with AON efficacy and efficiency (Table 7-3A) For Set B AONs, target sites of (++) AONs have statistically lower engaged scores than target sites of (–) AONs (Table 7-3B) Upon omission of four outlier AONs (6% of total AONs, i.e., H30A, H58A, H64A and H34A2), L3 scores can statistically differentiate efficacy between (+ 1) and (–) AONs, and efficiency between (++) and (+ 2) AONs Overall, L3 scores correlate efficacies and efficiencies of (++), (+) and (+ 1) AONs better than L1 scores (Table 7-2B versus Table 7-3B): L3 scores can differentiate between more AON grades than L1 scores; and for K-S tests in 142 which L1 scores show statistical significance, the corresponding K-S tests of L3 score achieve even lower p-values Table 7-3 p-values for K-S tests using the third level score (L3) p-values (with outliers: columns and 3; without outliers: columns and 5) of the K-S tests for the target sites of AONs in (A) Set A and (B) Set B Statistically significant p-values are indicated in bold and underlined Column describes the test case The last column indicates whether the particular test case tests for AON efficacy and/or efficiency In (B), (+ 1,2) denotes AONs merged from (+ 1) and (+ 2) AONs Note: Wilcoxon rank-sum test cannot be used as one of its key assumptions is violated, i.e., distributions of each AON grade’s L3 scores are distinct (box plots not shown) A B With outliers Without outliers Ho : H o: Ho : Ho : 1st < 2nd 1st > 2nd 1st < 2nd 1st > 2nd 0.81 0.030 0.0044 (++) vs (–) 0.92 0.28 0.67 0.51 (+) vs (–) 0.49 0.10 0.85 (++, +) vs (–) 0.35 0.82 0.98 0.0014 (++) vs (+) 0.0025 0.76 0.00063 (++) vs (+, –) 0.0035 Test case: 1st vs 2nd With outliers Without outliers Ho : Ho : Ho : Ho : 1st < 2nd 1st > 2nd 1st < 2nd 1st > 2nd 0.92 0.032 0.011 (++) vs (–) 0.060 0.81 0.97 0.035 (+1, 2) vs (–) 0.87 0.011 (++, +1, 2) vs (–) 0.029 0.061 0.84 0.032 (+ ) vs (–) 0.19 0.72 0.17 0.49 (+ ) vs (–) 0.31 0.95 0.14 (++) vs (+1, 2) 0.32 0.96 0.27 0.99 (++) vs (+ ) 0.23 0.77 0.027 (++) vs (+2) 0.59 0.61 0.17 0.99 (+1) vs (+2) 0.98 0.057 (++) vs (+1, 2, –) 0.18 Test case: 1st vs 2nd Test For Efficacy Efficacy Efficacy Efficacy Efficacy Test for Efficacy Efficacy Efficacy Efficacy Efficacy Efficiency Efficiency Efficiency Efficiency Both To explain the contrast between K-S test results of the first and third level scores, quartiles of the normalized L1 (L1) and L3 (L3) scores of AON target sites for AONs in each grade of Sets A and B are plotted for comparison; for example, the L1 score of an AON target site is the relative percentage difference between its L1 score and the average L1 score of all AON target sites As shown in Figure 7-5, L3 quartile 143 scores of target sites in (++) AONs are 34% to 124% lower than (–) AONs in Set A while L3 quartile scores of target sites in (++) AONs are 127% to 229% lower than (– ) AONs in Set B In contrast, L1 quartile scores of target sites in (++) and (–) AONs are similar in Set A whereas L1 quartile scores of target sites in (++) AONs are only 20% to 32% higher than (–) AONs in Set B Thus, L3 scores differ more extensively than L1 scores between target sites of efficient and inefficient AONs in Sets A and B Nevertheless, L3 scores cannot differentiate between (+) and (─) AON target sites Intriguingly, p-value for (++) versus (+) AONs is even smaller than for (++) versus (─) AONs, which suggests that although (+) AON target sites have more engaged nucleotides than (─) AON target sites, they can still induce exon skipping albeit not efficiently Hence, a more detail analysis is needed to explain this phenomenon, as described in the next section A L1 ++ + – Q1 ++ + – ++ + – Q3 Median -6 80 L3 10 -60 B L1 10 ++ +1 +2 – ++ +1 +2 – ++ +1 +2 – -10 Q1 Median Q3 -30 230 L3 160 90 20 -50 144 Figure 7-5 Normalized L1 and L3 quartile scores compared among AON grades The quartiles (Q1, median and Q3) of the normalized first level scores (L1), and normalized third level scores (L3) for target sites of AONs in each AON grade of (A) Set A and (B) Set B are plotted Refer to main text for the determination of these normalized scores The units for all the vertical axes are in percentages 7.5 Fourth level analysis: Localization of engaged nucleotides While third level analysis primarily involves a mean measure of frequency of engaged nucleotides, fourth level analysis includes consideration of localization of consecutive engaged nucleotides in the sequence of steps of transcriptional analysis of an AON target site Three fourth level scores are developed for this analysis: (1) L4_AVG = (7-1) Sum of nucleotide engaged scores for the group of consecutive nucleotides Number of nucleotides in the group (2) L4_AND = (7-2) Sum of steps of transcriptional analysis in which all the nucleotides in the group of consecutive nucleotides are engaged simultaneously (see Figure 7-4) Total number of steps of transcriptional analysis (3) L4_OR = (7-3) Sum of steps of transcriptional analysis in which at least one nucleotide in the group of consecutive nucleotides is engaged (see Figure 7-4) Total number of steps of transcription analysis For each AON target site analyzed, all possible groups of to consecutive nucleotides are obtained; each target site could have more than one such groups For instance, groups of two consecutive nucleotides are extracted by walking one nucleotide at a time from one end of an AON target site to the other end Likewise, 145 groups of three to five consecutive nucleotides are obtained similarly; inadequate sample size constrained the analysis to a maximum of five consecutive nucleotides Subsequently, the three fourth level scores are applied on every group of consecutive nucleotides and correlated with AON efficacy and efficiency by K-S tests among various AON grades in Sets A and B The analyses reveal that the localization of consecutive engaged nucleotides at the ends of an AON target site attenuates AON efficacy and efficiency more than at other sites, as discussed below 7.5.1 Engaged nucleotides away from the ends of an AON target site For the purpose of this analysis, “away from the ends of an AON target site” refers to nucleotides in the target site that are at least four nucleotides away from both 3’ and 5’ ends, as illustrated in Figure 7-4 The three fourth level scores are computed only for those groups of consecutive nucleotides in which every nucleotide in the group has an engaged score of at least 0.1 The analyses were stratified according to the number of consecutive nucleotides in the groups Groups of two consecutive nucleotides For both Sets A and B AONs, the K-S tests find no statistical differences in all three scores of AON target sites at the different AON grades (data not shown) Note: inadequate AON sample size in Set B restricts the tests to scores of target sites of (++) versus (+ 1) AONs and (++) versus (+ 1,2 , –) AONs 146 Groups of three consecutive nucleotides K-S tests cannot be performed for both sets, as AON sample sizes of many AON grades are inadequate ( 2nd 0.0089 0.97 0.055 0.96 0.96 0.013 0.17 0.98 0.95 0.025 0.91 0.017 0.94 0.012 0.11 0.96 0.16 0.96 L4_AND Ho : H o: 1st < 2nd 1st > 2nd 0.97 0.028 0.97 0.039 0.093 0.96 0.98 0.036 0.11 0.97 0.055 0.91 0.17 0.66 0.088 0.96 0.11 0.99 L4_OR Ho : H o: 1st < 2nd 1st > 2nd 0.0019 0.96 0.96 0.014 0.0035 0.96 0.31 0.93 0.082 0.82 0.017 0.86 0.020 0.96 0.026 0.94 0.047 Test for Efficacy Efficacy Both Efficiency Both Efficacy Both Efficacy Efficacy 150 D B (++) vs (+1,2, –) 0.018 A 3' vs 5' (++) 0.028 0.96 0.79 0.25 0.24 0.44 0.040 0.060 0.96 0.89 Both Efficiency Overall, target sites of efficient AONs have lowest L4_OR scores in Set A while they have lowest L4_AVG scores in Set B, which indicates that only one nucleotide at the ends of an AON target site that is engaged at considerable steps of transcriptional analysis is sufficient to attenuate AON efficacy and efficiency This is in stark contrast to the case where engaged nucleotides are localized away from the ends of AON target sites in which at least three consecutive nucleotides that are engaged simultaneously at considerable steps of transcriptional analysis would attenuate AON efficacy and efficiency Taken together, AON efficacy and efficiency is more attenuated by presence of engaged nucleotides at the ends of target sites than at other sites 7.6 Efficiency of short AONs is attenuated more by engaged nucleotides Results in Section 7.5.2 suggest that the efficacy and efficiency of short AONs (Set A) are more attenuated by engaged nucleotides at 3’ or 5’ ends of the target site as compared to longer AONs (Set B) Particularly, the L4_OR and L4_AVG scores demonstrate the best correlative power in Set A and Set B (Tables 7-4A to 7-4C), respectively As L4_AVG is the mean nucleotide engaged score of the nucleotides at 3’ or 5’ ends of the target site, its magnitude increases when the nucleotides are engaged at more steps of transcriptional analysis In contrast, because L4_OR 151 measures the steps of transcriptional analysis at which at least one nucleotide at 3’ or 5’ ends of the target site is engaged, it can have a high value albeit the individual nucleotide engaged scores are low Therefore, efficacy and efficiency of Set A AONs (short) are attenuated under fewer incidences of nucleotides being engaged at steps of transcriptional analysis than Set B AONs (long) To eliminate the possibility that this deduction is due to differences in the frequency and localization of engaged nucleotides between Sets A and B AON target sites, their third and fourth level scores are compared using K-S tests, and no statistical difference is detected (Appendix A19) Notably, augmentation of AON efficiency by targeting longer target sites in dystrophin pre-mRNA has been reported (Harding et al., 2007) Moreover, engaged nucleotides at 3’ end of shorter target sites (Set A) attenuated AON efficiency more than at 5’ end (Table 7-4D) This might explain why AON efficiency is reported to be more sensitive to nucleotide changes at the 3’ end than 5’ end of its target site (Sczakiel, 2000) 7.7 Correlative power of the fourth level scores To demonstrate the correlative power of the fourth level scores, three representative examples in which only the fourth level scores can differentiate (++) AONs in Set A are discussed Figure 7-7A illustrated an example wherein AON target sites with identical accessibility scores (L1) can have strikingly different engaged scores (L3) Whereas the (–) AON target site’s high L3 score was expected, the higher L3 score of the (++) AON target site compared to the (+) AON target site was confounding 152 However, analysis at the fourth level reveals that more engaged nucleotides are localized at the ends of (+) AON target site than at (++) AON target site Figure 7-7B illustrated an example in which L3 scores of the target site correlate inversely with AON efficacy and efficiency, i.e., target sites of AONs with higher engaged scores have higher efficiency to induce exon skipping Again, the fourth level analysis resolved this conundrum Although the (++) AON target has the most engaged nucleotides among them, they are mostly localized away from the ends of the sites where at least three consecutive nucleotides that are engaged simultaneously at considerable steps of transcriptional analysis is needed to attenuate AON efficiency Conversely, although the (–) AON target site has the least engaged nucleotides among them, they are mostly localized at the 3’ end of the site where they are especially detrimental to AON efficiency The final example (Figure 7-7C) illustrated a widespread phenomenon in the data set in which (+) AON target sites have higher L3 scores than (─) AON target sites but yet could still induce exon skipping In fact, this phenomenon caused the pvalues of K-S tests of (++) versus (+) AON target site L3 scores to be smaller than for (++) versus (─) target site L3 scores (Table 7-3A of Section 7.4) In most instances, most of the engaged nucleotides manifested in (+) AON target sites are localized away from the ends of the sites Altogether, these examples show that localization is as important as the frequency of engaged nucleotides As a further illustration, a novel AON target sequence was selected to skip exon 57, which has been deemed to be “unskippable” (Aartsma-Rus et al., 2005) 153 Interestingly, exon 57 manifests an overwhelming occurrence of engaged nucleotides (Appendix A-20); hence, it is relatively difficult to locate a suitably long sequence that has ESE activity as well as high co-transcriptional binding accessibility In fact, published AONs targeting this exon have target sites that manifest high L3 and L4 scores Based on the insights obtained in the analyses, the novel AON target site is determined by these rules: negligible occurrence of engaged nucleotides (low L3 and L4 scores), presence of ESE motifs predicted by ESE-Finder (Cartegni et al., 2003) and RESCUE-ESE (Fairbrother et al., 2002), and location at the first half of the exon Experimental validation shows that it is indeed able to induce the skipping exon 57 (Figure of Wee et al., 2008a as attached in Appendix A-1); more validations to target exon 51 are published at Wee et al (2007) 154 h78AON2 (++) h56AON3 (+) h43AON1 (–) A L1 L3 L4_OR 0.44 0.024 0.0082 0.13 5’: 0.031 3’: 0.003 5’: 0.066 3’: 0.35 5’: 0.86 h50AON1 (++) h41AON2 (+) h58AON1 (–) B L3 L4_OR 0.013 0.096 0.058 3’: 0.004 3’: 0.058 5’: 0.011 3’: 0.83 h40AON1 (++) h42AON2 (+) h43AON4 (–) C L3 L4_OR < 0.001 0.14 0.099 5’: 0.004 3’: 0.059 5’: 0.031 3’: 0.91 5’: 0.38 Figure 7-7 Demonstration of the correlative power of the fourth level scores Three examples where only the fourth level scores can correlate AON efficacy and efficiency compared to the third level score (see text for details) (A) to (C) In each example, the incidences of engaged nucleotides at each step of transcriptional analysis for all nucleotide in the AON target sites were depicted 7.8 Summary Previous studies have supported the general principle that mRNA secondary structures influence AON efficacy and efficiency (Vickers et al., 2000; Lehmann et 155 al., 2000; Kretschmer-Kazemi and Sczakiel, 2003), although these studies did not consider co-transcriptional folding in the prediction of the secondary structures However, laboratories working in this field (Aartsma-Rus et al., 2005; Harding et al., 2007) have reported no correlation with secondary mRNA structure in designing AONs to induce exon skipping of the dystrophin gene In these reports, co- transcriptional dynamic changes in secondary structure are not considered This shortcoming is overcome in this study by using a model to approximate cotranscriptional dynamic changes in pre-mRNA secondary structures and by developing novel scoring methodologies to measure dynamic changes in the binding accessibilities of AON target sites in the co-transcriptional process Applying four levels of analysis with scoring methodologies of increasing complexity, the frequency and localization of consecutive engaged nucleotides in the sequence of steps of transcriptional analysis could correlate with efficacy and efficiency of 94% of previously reported AONs Four key novel insights pertaining to AON efficacy and efficiency are deduced from this study Firstly, the lowest frequencies of engaged nucleotides manifested at target sites are associated with the most efficient (++) AONs Secondly, engaged nucleotides at 3’ or 5’ ends of the target site attenuate AON efficacy and efficiency more than at other sites Thirdly, the efficacy and efficiency of longer AONs are less attenuated by engaged nucleotides at 3’ or 5’ ends of the target site as compared to shorter AONs, which is in agreement with experimental observations (Harding et al., 2007) Fourthly, engaged nucleotides at 3’ end of a short target site attenuate AON efficiency more than at 5’ end, which also agrees with experimental observations (Sczakiel, 2000) 156 ... 0 .7 0 .7 0 .7 0.6 0.6 0.6 0.5 0.5 0.5 0.4 0.4 0.4 0.3 0.3 0.3 0.2 0.2 0.2 0.1 0.1 0 90 92 94 96 98 100 102 104 106 108 0.1 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 19 20 21 22 23 24 25 26 27. .. only 17% of target sites of (+) AONs had one or more clusters, they were manifested in 52% of target sites of (++) AONs Set B also exhibited similar trends: 71 %, 70 % and 80% of target sites of (–)... 5th-percentile of L3 scores of (++) AON target sites (Appendix A-18) On the other hand, target sites of h45AON5 and h46AON4 graded as (+) and target sites of h51AON29, h55AON5 and h77AON2 graded