Identification of sequence motifs significantly associated with antisense activity

Kyle A Mcquisten,Andrew S Peek

doi:10.1186/1471-2105-8-184

Abstract

BackgroundPredicting the suppression activity of antisense oligonucleotide sequences is the main goal of the rational design of nucleic acids. To create an effective predictive model, it is important to know what properties of an oligonucleotide sequence associate significantly with antisense activity. Also, for the model to be efficient we must know what properties do not associate significantly and can be omitted from the model. This paper will discuss the results of a randomization procedure to find motifs that associate significantly with either high or low antisense suppression activity, analysis of their properties, as well as the results of support vector machine modelling using these significant motifs as features.ResultsWe discovered 155 motifs that associate significantly with high antisense suppression activity and 202 motifs that associate significantly with low suppression activity. The motifs range in length from 2 to 5 bases, contain several motifs that have been previously discovered as associating highly with antisense activity, and have thermodynamic properties consistent with previous work associating thermodynamic properties of sequences with their antisense activity. Statistical analysis revealed no correlation between a motif's position within an antisense sequence and that sequences antisense activity. Also, many significant motifs existed as subwords of other significant motifs. Support vector regression experiments indicated that the feature set of significant motifs increased correlation compared to all possible motifs as well as several subsets of the significant motifs.ConclusionThe thermodynamic properties of the significantly associated motifs support existing data correlating the thermodynamic properties of the antisense oligonucleotide with antisense efficiency, reinforcing our hypothesis that antisense suppression is strongly associated with probe/target thermodynamics, as there are no enzymatic mediators to speed the process along like the RNA Induced Silencing Complex (RISC) in RNAi. The independence of motif position and antisense activity also allows us to bypass consideration of this feature in the modelling process, promoting model efficiency and reducing the chance of overfitting when predicting antisense activity. The increase in SVR correlation with significant features compared to nearest-neighbour features indicates that thermodynamics alone is likely not the only factor in determining antisense efficiency.

Highlights

Predicting the suppression activity of antisense oligonucleotide sequences is the main goal of the rational design of nucleic acids
When looking at the subword makeup of the significant motifs, we found that of the 167 motifs associated with effective antisense activity, 70 of them contained submotifs that were associated with ineffective antisense activity
In order to complete our desired task of determining motifs that significantly associate with antisense effectiveness/ineffectiveness, we developed a Monte Carlo randomization procedure to systematically determine if a wide range of motifs were overrepresented in either effective or ineffective antisense sequences

Summary

Introduction

Predicting the suppression activity of antisense oligonucleotide sequences is the main goal of the rational design of nucleic acids. To create an effective predictive model, it is important to know what properties of an oligonucleotide sequence associate significantly with antisense activity. Studies of possible target sites for antisense suppression have shown that not all oligonucleotide sequences are effective in inducing suppression, with many sequences not inducing suppression at all. This kind of exhaustive experimental screening is prohibitively expensive and time consuming, which makes a computational model that relates oligonucleotide sequence to suppression activity desirable. A small number of subsequence motifs have been identified as associating significantly with antisense activity [7,13], but a broad survey over motifs of different lengths using a publicly available dataset has not been performed until now. We have used a randomization procedure to assess the association of a large number of motifs with antisense activity

Methods

Results

Discussion

Conclusion