Artificial microRNA mediated gene silencing in plants: progress and perspectives

Tiwari, Manish; Sharma, Deepika; Trivedi, Prabodh Kumar

doi:10.1007/s11103-014-0224-7

Cited by 126 publications

(71 citation statements)

References 123 publications

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“…Host plants do not normally utilize the miRNA pathway, unlike siRNAs, during antiviral functions; therefore, plant viruses have not evolved counter-measures to avoid the surveillance of the miRNA pathways (Martínez et al 2013). The amiRNA-mediated gene silencing has become an effective and versatile technique to engineer virus-resistant transgenic plants due to its safety, specificity and efficiency (Niu et al 2006;Qu et al 2007;Castanotto and Rossi 2009;Tiwari et al 2014). Researchers have developed resistance against RSV and RBSDV in rice plants by introducing dsRNAs that target RSV genes (Ma et al 2011;Shimizu et al 2011b;Jiang et al 2013) and RBSDV genes (Shimizu et al 2011a).…”

Section: Discussionmentioning

confidence: 99%

Dimeric artificial microRNAs mediate high resistance to RSV and RBSDV in transgenic rice plants

Sun

Lin

et al. 2016

Plant Cell Tiss Organ Cult

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Infection of rice with Rice stripe virus (RSV) and Rice black streaked dwarf virus (RBSDV) causes a significant loss of grain production. Due to the lack of natural resistance resources against these viruses, it is imperative to discover a biotechnological approach that will provide effective and safe immunity to RSV and RBSDV. In this study, we constructed three dimeric artificial microRNA (amiRNA) precursor expression vectors (pamiR-M, pamiR-3 and pamiR-U) that simultaneously target the CP genes of RSV and RBSDV based on the structure of the rice (Oryza sativa L.) osa-MIR528 precursor. The transgenic plants were obtained by Agrobacterium tumefaciens-mediated transformation and were shown to express amiRNAs successfully. Viral challenge assays revealed that these transgenic plants demonstrated different resistance (26.66-54.17 %) against RSV and RBSDV infection simultaneously. The amiRNA-targeting 3 0 -UTR region of CP gene (pamiR-U) induced higher virus resistance: 54.17 % against RSV and 45.83 % against RBSDV. A northern blot assay indicated that there was a good correlation between the resistance level and amiRNAs accumulation. The RNA silencing induced by the original amiRNAs could be bilaterally extended by the siRNA pathway. The amiRNAs, together with the secondary siRNAs, mediated the degradation of viral RNAs. A genetic stability assay showed that transgenes and amiRNA-mediated virus resistance could be stably inherited in the transgenic plants.

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Section: Discussionmentioning

confidence: 99%

Dimeric artificial microRNAs mediate high resistance to RSV and RBSDV in transgenic rice plants

Sun

Lin

et al. 2016

Plant Cell Tiss Organ Cult

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“…amiRNAs can also be used to study the functions of multiple genes which share the same sequences making the functional analyses easy. Apart from this, amiRNA technology has proved to be a potential approach for engineering virus resistance in different plants, besides the improvement of several agronomically important traits by silencing of the appropriate gene(s) in plants by amiRNAs [41]. Viruses release RNAi suppressors in defense and hence the resistance is lost, and amiRNA has been used as an alternative for this defense mechanism.…”

Section: Discussionmentioning

confidence: 99%

Artificial miRNAs for Specific Gene Silencing and Engineering Virus Resistance in Plants

Rajam¹

2015

Cell Dev Biol

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“…61 Similarly, artificial small interfering RNA and microRNA have been widely used in plant systems to reduce gene expression. 62 Achieving stable gene integration in higher plants can be problematic. An alternative is to employ viral-induced gene silencing approaches.…”

Section: Manipulating Gene Expressionmentioning

confidence: 99%

Designing metabolic engineering strategies with genome-scale metabolic flux modeling

Yen¹,

Tanniche²,

Fisher³

et al. 2015

AGG

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New in silico tools that make use of genome-scale metabolic flux modeling are improving the design of metabolic engineering strategies. This review highlights the latest developments in this area, explains the interface between these in silico tools and the experimental implementation tools of metabolic engineers, and provides a way forward so that in silico predictions can better mimic reality and more experimental methods can be considered in simulation studies. The several methodologies for solving genome-scale models (eg, flux balance analysis [FBA], parsimonious FBA, flux variability analysis, and minimization of metabolic adjustment) all have unique advantages and applications. There are two basic approaches to designing metabolic engineering strategies in silico, and both have demonstrated success in the literature. The first involves: 1) making a genetic manipulation in a model; 2) testing for improved performance through simulation; and 3) iterating the process. The second approach has been used in more recently designed in silico tools and involves: 1) comparing metabolic flux profiles of a wild-type and ideally engineered state and 2) designing engineering strategies based on the differences in these flux profiles. Improvements in genome-scale modeling are anticipated in areas such as the inclusion of all relevant cellular machinery, the ability to understand and anticipate the results of combinatorial enrichment experiments, and constructing dynamic and flexible biomass equations that can respond to environmental and genetic manipulations. A brief introduction to genome-scale metabolic flux modelingA "genome-scale" metabolic flux model (GEM) consists of a network of biochemical reactions that is reconstructed based on the genomic sequence and annotation of a cell. Assuming a "steady-state" metabolism (ie, a snapshot of metabolism at one time point) is reached on a short time-scale, these reactions can be represented by a linear system of equations. Then, problems such as maximizing specific chemical production or growth can be solved efficiently by linear programming. GEMs and their uses have been reviewed thoroughly, and they are most basically used to predict reaction flux, which is the overall rate of metabolite conversion. 1,2 Often, laboratory measurements including the rates of substrate consumption, product formation, and growth are used as model constraints so calculations coincide with observations. Other model constraints can be derived from reaction thermodynamics, 3 cellular regulatory networks, 4 and -omics datasets. 5 GEMs have been constructed and utilized for intensively

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Artificial microRNA mediated gene silencing in plants: progress and perspectives

Cited by 126 publications

References 123 publications

Dimeric artificial microRNAs mediate high resistance to RSV and RBSDV in transgenic rice plants

Dimeric artificial microRNAs mediate high resistance to RSV and RBSDV in transgenic rice plants

Artificial miRNAs for Specific Gene Silencing and Engineering Virus Resistance in Plants

Designing metabolic engineering strategies with genome-scale metabolic flux modeling

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