Dataset Information

Integrated siRNA design based on surveying of features associated with high RNAi effectiveness.

ABSTRACT:

Background

Short interfering RNAs have allowed the development of clean and easily regulated methods for disruption of gene expression. However, while these methods continue to grow in popularity, designing effective siRNA experiments can be challenging. The various existing siRNA design guidelines suffer from two problems: they differ considerably from each other, and they produce high levels of false-positive predictions when tested on data of independent origins.

Results

Using a distinctly large set of siRNA efficacy data assembled from a vast diversity of origins (the siRecords data, containing records of 3,277 siRNA experiments targeting 1,518 genes, derived from 1,417 independent studies), we conducted extensive analyses of all known features that have been implicated in increasing RNAi effectiveness. A number of features having positive impacts on siRNA efficacy were identified. By performing quantitative analyses on cooperative effects among these features, then applying a disjunctive rule merging (DRM) algorithm, we developed a bundle of siRNA design rule sets with the false positive problem well curbed. A comparison with 15 online siRNA design tools indicated that some of the rule sets we developed surpassed all of these design tools commonly used in siRNA design practice in positive predictive values (PPVs).

Conclusion

The availability of the large and diverse siRNA dataset from siRecords and the approach we describe in this report have allowed the development of highly effective and generally applicable siRNA design rule sets. Together with ever improving RNAi lab techniques, these design rule sets are expected to make siRNAs a more useful tool for molecular genetics, functional genomics, and drug discovery studies.

SUBMITTER: Gong W

PROVIDER: S-EPMC1698580 | biostudies-literature | 2006 Nov

REPOSITORIES: biostudies-literature

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Publications

Integrated siRNA design based on surveying of features associated with high RNAi effectiveness.

Gong Wuming W Ren Yongliang Y Xu Qiqi Q Wang Yejun Y Lin Dong D Zhou Haiyan H Li Tongbin T

BMC bioinformatics 20061127

<h4>Background</h4>Short interfering RNAs have allowed the development of clean and easily regulated methods for disruption of gene expression. However, while these methods continue to grow in popularity, designing effective siRNA experiments can be challenging. The various existing siRNA design guidelines suffer from two problems: they differ considerably from each other, and they produce high levels of false-positive predictions when tested on data of independent origins.<h4>Results</h4>Using ...[more]

PMID: 17129386

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Project description:BackgroundSmall interfering RNAs (siRNAs) have become an important tool in cell and molecular biology. Reliable design of siRNA molecules is essential for the needs of large functional genomics projects.ResultsTo improve the design of efficient siRNA molecules, we performed a comparative, thermodynamic and correlation analysis on a heterogeneous set of 653 siRNAs collected from the literature. We used this training set to select siRNA features and optimize computational models. We identified 18 parameters that correlate significantly with silencing efficiency. Some of these parameters characterize only the siRNA sequence, while others involve the whole mRNA. Most importantly, we derived an siRNA position-dependent consensus, and optimized the free-energy difference of the 5' and 3' terminal dinucleotides of the siRNA antisense strand. The position-dependent consensus is based on correlation and t-test analyses of the training set, and accounts for both significantly preferred and avoided nucleotides in all sequence positions. On the training set, the two parameters' correlation with silencing efficiency was 0.5 and 0.36, respectively. Among other features, a dinucleotide content index and the frequency of potential targets for siRNA in the mRNA added predictive power to our model (R = 0.55). We showed that our model is effective for predicting the efficiency of siRNAs at different concentrations. We optimized a neural network model on our training set using three parameters characterizing the siRNA sequence, and predicted efficiencies for the test siRNA dataset recently published by Novartis. On this validation set, the correlation coefficient between predicted and observed efficiency was 0.75. Using the same model, we performed a transcriptome-wide analysis of optimal siRNA targets for 22,600 human mRNAs.ConclusionWe demonstrated that the properties of the siRNAs themselves are essential for efficient RNA interference. The 5' ends of antisense strands of efficient siRNAs are U-rich and possess a content similarity to the pyrimidine-rich oligonucleotides interacting with the polypurine RNA tracks that are recognized by RNase H. The advantage of our method over similar methods is the small number of parameters. As a result, our method requires a much smaller training set to produce consistent results. Other mRNA features, though expensive to compute, can slightly improve our model.

Project description:BackgroundPrevious research has not provided enough direction regarding effective content design of courses integrating the humanities and social sciences in medical and dental education. This study aims at exploring how an Integrated Medical/Dental Humanities-Social Medicine/Dentistry course may be designed; how effective it may be in terms of student growth in knowledge, attitudes, skills, and aspirations; and associated factors.MethodsThe course was designed by distilling commonalities in the international standards for medical/dental education proposed by seven major health organizations. This analysis resulted in a curriculum covering nine major topics: history, professionalism, communication, ethics, management, policy, insurance, law, and research methodology. During the 2017 calendar year, data was collected and statistically analyzed from 68 third-year pre-doctoral students enrolled in the resulting MDHS 13-week course.ResultsParticipants showed growth in skills, aspirations, knowledge, and attitudes, with the greatest change occurring in skills, then aspirations, knowledge, and attitudes. Knowledge growth was the only variable significantly related to student achievement of course objectives (β = 0.635, t (63) = 3.394, p = 0.001). The topics that students perceived as most critical were insurance, policy, management, and law. The perceived importance of research was most common among participants and was significantly related to all learning outcomes (For knowledge, β = 0.213, t (63) = 2.203, p = 0.031; for attitudes, β = 0.784, t (63) = 10.257, p = 0.000; for skills, β = 0.769, t (63) = 9.772, p = 0.000; and aspirations β = 0.639, t (63) = 7.595, p = 0.000).ConclusionsThis study proposed a framework for humanities-social sciences education in health sciences education and analyzed its implementation. The empirical evaluation of its effectiveness and factors related to successful outcomes found that students perceived gains in their knowledge, attitudes, skills, and aspirations for humanistic and social aspects of dentistry/medicine. In addition, their recognition of the importance of research was associated with the greatest growth in all four learning outcomes. This study may contribute to the improved design of integrated humanities-social sciences courses.

Dataset Information

Integrated siRNA design based on surveying of features associated with high RNAi effectiveness.

Background

Results

Conclusion

Publications

Integrated siRNA design based on surveying of features associated with high RNAi effectiveness.

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