Chapter title |
Bioinformatics Tools for Achieving Better Gene Silencing in Plants.
|
---|---|
Chapter number | 3 |
Book title |
Plant Gene Silencing
|
Published in |
Methods in molecular biology, February 2015
|
DOI | 10.1007/978-1-4939-2453-0_3 |
Pubmed ID | |
Book ISBNs |
978-1-4939-2452-3, 978-1-4939-2453-0
|
Authors |
Firoz Ahmed, Xinbin Dai, Patrick Xuechun Zhao, Ahmed, Firoz, Dai, Xinbin, Zhao, Patrick Xuechun |
Editors |
Kirankumar S. Mysore, Muthappa Senthil-Kumar |
Abstract |
RNA interference (RNAi) is one of the most popular and effective molecular technologies for knocking down the expression of an individual gene of interest in living organisms. Yet the technology still faces the major issue of nonspecific gene silencing, which can compromise gene functional characterization and the interpretation of phenotypes associated with individual gene knockdown. Designing an effective and target-specific small interfering RNA (siRNA) for induction of RNAi is therefore the major challenge in RNAi-based gene silencing. A 'good' siRNA molecule must possess three key features: (a) the ability to specifically silence an individual gene of interest, (b) little or no effect on the expressions of unintended siRNA gene targets (off-target genes), and (c) no cell toxicity. Although several siRNA design and analysis algorithms have been developed, only a few of them are specifically focused on gene silencing in plants. Furthermore, current algorithms lack a comprehensive consideration of siRNA specificity, efficacy, and nontoxicity in siRNA design, mainly due to lack of integration of all known rules that govern different steps in the RNAi pathway. In this review, we first describe popular RNAi methods that have been used for gene silencing in plants and their serious limitations regarding gene-silencing potency and specificity. We then present novel, rationale-based strategies in combination with computational and experimental approaches to induce potent, specific, and nontoxic gene silencing in plants. |
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Members of the public | 1 | 100% |
Mendeley readers
Geographical breakdown
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Unknown | 17 | 100% |
Demographic breakdown
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Student > Ph. D. Student | 3 | 18% |
Other | 2 | 12% |
Researcher | 2 | 12% |
Student > Bachelor | 2 | 12% |
Lecturer | 1 | 6% |
Other | 2 | 12% |
Unknown | 5 | 29% |
Readers by discipline | Count | As % |
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Agricultural and Biological Sciences | 6 | 35% |
Biochemistry, Genetics and Molecular Biology | 3 | 18% |
Arts and Humanities | 1 | 6% |
Chemistry | 1 | 6% |
Engineering | 1 | 6% |
Other | 0 | 0% |
Unknown | 5 | 29% |