Next-generation sequencing is a robust strategy for the high-throughput detection of zygosity in transgenic maize
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Simple and reliable, high-throughput techniques to detect the zygosity of transgenic events in plants are valuable for biotechnology and plant breeding companies seeking robust genotyping data for the assessment of new lines and the monitoring of breeding programs. We show that next-generation sequencing (NGS) applied to short PCR products spanning the transgene integration site provides accurate zygosity data that are more robust and reliable than those generated by PCR-based methods. The NGS reads covered the 5′ border of the transgenic events (incorporating part of the transgene and the flanking genomic DNA), or the genomic sequences flanking the unfilled transgene integration site at the wild-type locus. We compared the NGS method to competitive real-time PCR with transgene-specific and wild-type-specific primer/probe pairs, one pair matching the 5′ genomic flanking sequence and 5′ part of the transgene and the other matching the unfilled transgene integration site. Although both NGS and real-time PCR provided useful zygosity data, the NGS technique was favorable because it needed fewer optimization steps. It also provided statistically more-reliable evidence for the presence of each allele because each product was often covered by more than 100 reads. The NGS method is also more suitable for the genotyping of large panels of plants because up to 80 million reads can be produced in one sequencing run. Our novel method is therefore ideal for the rapid and accurate genotyping of large numbers of samples.
KeywordsBreeding Genotyping High throughput Real-time PCR Transgenic plants
We acknowledge Raphael Soeur and Claudia Hansen (Fraunhofer IME, Aachen, Germany) for performing the next-generation sequencing and for the helpful discussions about sample processing and data management. We also acknowledge Euregio Analytik BioChem GmbH for cooperation in the project and for providing the template DNA material. We acknowledge Dow AgroSciences and KWS Saat AG for making the transgenic kernels/DNA available for the project. We acknowledge Dr. Richard M Twyman for editing the manuscript. This work is supported by the BMBF (0316075B).
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