Accurate measurement of transgene copy number in crop plants using droplet digital PCR
- PMID: 28231382
- DOI: 10.1111/tpj.13517
Accurate measurement of transgene copy number in crop plants using droplet digital PCR
Abstract
Genetic transformation is a powerful means for the improvement of crop plants, but requires labor- and resource-intensive methods. An efficient method for identifying single-copy transgene insertion events from a population of independent transgenic lines is desirable. Currently, transgene copy number is estimated by either Southern blot hybridization analyses or quantitative polymerase chain reaction (qPCR) experiments. Southern hybridization is a convincing and reliable method, but it also is expensive, time-consuming and often requires a large amount of genomic DNA and radioactively labeled probes. Alternatively, qPCR requires less DNA and is potentially simpler to perform, but its results can lack the accuracy and precision needed to confidently distinguish between one- and two-copy events in transgenic plants with large genomes. To address this need, we developed a droplet digital PCR-based method for transgene copy number measurement in an array of crops: rice, citrus, potato, maize, tomato and wheat. The method utilizes specific primers to amplify target transgenes, and endogenous reference genes in a single duplexed reaction containing thousands of droplets. Endpoint amplicon production in the droplets is detected and quantified using sequence-specific fluorescently labeled probes. The results demonstrate that this approach can generate confident copy number measurements in independent transgenic lines in these crop species. This method and the compendium of probes and primers will be a useful resource for the plant research community, enabling the simple and accurate determination of transgene copy number in these six important crop species.
Keywords: Citrus sinensis; Oryza sativa; Solanum lycopersicum; Solanum tuberosum; Triticum aestivum; Zea mays; droplet digital PCR; transgene copy number.
Published 2017. This article is a U.S. Government work and is in the public domain in the USA.
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