The expanding use of RNA interference (RNAi) in agricultural biotechnology necessitates tools for characterizing and quantifying double-stranded RNA (dsRNA)-containing transcripts that are expressed in transgenic plants. We sought to detect and quantify such transcripts in transgenic maize lines engineered to control western corn rootworm (Diabrotica virgifera virgifera LeConte) via overexpression of an inverted repeat sequence bearing a portion of the putative corn rootworm orthologue of yeast Snf7 (DvSnf7), an essential component of insect cell receptor sorting. A quantitative assay was developed to detect DvSnf7 sense strand-containing dsRNA transcripts that is based on the QuantiGene Plex 2.0 RNA assay platform from Affymetrix. The QuantiGene assay utilizes cooperative binding of multiple oligonucleotide probes with specificity for the target sequence resulting in exceptionally high assay specificity. Successful implementation of this assay required heat denaturation in the presence of the oligonucleotide probes prior to hybridization, presumably to dissociate primary transcripts carrying the duplex dsRNA structure. The dsRNA assay was validated using a strategy analogous to the rigorous enzyme-linked immunosorbent assay evaluations that are typically performed for foreign proteins expressed in transgenic plants. Validation studies indicated that the assay is sensitive (to 10 pg of dsRNA/g of fresh tissue), highly reproducible, and linear over ∼2.5 logs. The assay was validated using purified RNA from multiple maize tissue types, and studies indicate that the assay is also quantitative in crude tissue lysates. To the best of our knowledge, this is the first report of a non-polymerase chain reaction-based quantitative assay for dsRNA-containing transcripts, based on the use of the QuantiGene technology platform, and will broadly facilitate characterization of dsRNA in biological and environmental samples.

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Evaluation Study | Journal Article

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Armstrong TA, Chen H, Ziegler TE, Iyadurai KR, Gao AG, Wang Y, Song Z, Tian Q, Zhang Q, Ward JM, ... Show all

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