Comprehensive Protein-Based Artificial MicroRNA Screens for Effective Gene Silencing in Plants
Comprehensive Protein-Based Artificial MicroRNA Screens for Effective Gene Silencing in Plants
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DOI：
10.1105/tpc.113.112235
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发表时间：
2013-05-01
期刊：
影响因子：
11.6
通讯作者：
Sheen, Jen
中科院分区：
文献类型：
--
作者：
Li, Jian-Feng;Chung, Hoo Sun;Sheen, Jen
人工microRNA(AmiRNA)方法为在任何植物物种中进行靶向基因操作提供了一种强大的策略。然而，目前amRNA疗效的不可预测性限制了这项有前途的技术的广泛应用。为了解决这一问题，我们开发了基于表位标记的amiRNA(ETPamir)筛选，在该筛选中，编码表位标记的蛋白质的靶mRNAs在原生质体中结构性或诱导性地与针对单个或多个基因的amiRNA候选者共表达。这一设计允许对目标蛋白质和mRNAs进行平行定量，以确定amiRNA的有效性和作用机制，从而绕过不可预测的amiRNA表达/处理和抗体不可得性。对79个ETPamir筛选的16个靶基因中的63个amiRNAs的系统评价揭示了一个简单、有效的解决方案，可以从数百个计算预测中选择最佳的amiRNAs，达到类似于植物细胞中100%的基因沉默和转基因植物中的零表型。最优的amiRNAs主要介导59个编码区的高度特异性翻译抑制，并有有限的mRNA衰退或切割。我们的筛选可以很容易地应用于不同的植物物种，包括拟南芥、烟草、番茄、向日葵、长春花、玉米和水稻，并有效验证了预测的天然miRNA靶标。这些筛选可以通过使amiRNA成为一种更可预测和更易于管理的遗传和功能基因组技术来改进植物研究和作物工程。
Artificial microRNA (amiRNA) approaches offer a powerful strategy for targeted gene manipulation in any plant species. However, the current unpredictability of amiRNA efficacy has limited broad application of this promising technology. To address this, we developed epitope-tagged protein-based amiRNA (ETPamir) screens, in which target mRNAs encoding epitope-tagged proteins were constitutively or inducibly coexpressed in protoplasts with amiRNA candidates targeting single or multiple genes. This design allowed parallel quantification of target proteins and mRNAs to define amiRNA efficacy and mechanism of action, circumventing unpredictable amiRNA expression/processing and antibody unavailability. Systematic evaluation of 63 amiRNAs in 79 ETPamir screens for 16 target genes revealed a simple, effective solution for selecting optimal amiRNAs from hundreds of computational predictions, reaching similar to 100% gene silencing in plant cells and null phenotypes in transgenic plants. Optimal amiRNAs predominantly mediated highly specific translational repression at 59 coding regions with limited mRNA decay or cleavage. Our screens were easily applied to diverse plant species, including Arabidopsis thaliana, tobacco (Nicotiana benthamiana), tomato (Solanum lycopersicum), sunflower (Helianthus annuus), Catharanthus roseus, maize (Zea mays) and rice (Oryza sativa), and effectively validated predicted natural miRNA targets. These screens could improve plant research and crop engineering by making amiRNA a more predictable and manageable genetic and functional genomic technology.