Use of NGS combined to enrichment technologies for GMO detection
- Debode, F. , Hulin, J. , Charloteaux, B. , Coppieters, W. , Hanikenne, M. & Berben, G. (2017). Use of NGS combined to enrichment technologies for GMO detection. Jana Pulkrabová, Monika Tomaniová, Michel Nielen and Jana Hajšlová. Proceedings in: 8th International Symposium on Recent Advances in Food Analysis, Prague, Czech Republic, November 7–10, 2017, 127.
|Year of conference
|Use of NGS combined to enrichment technologies for GMO detection
|Jana Pulkrabová, Monika Tomaniová, Michel Nielen and Jana Hajšlová
|8th International Symposium on Recent Advances in Food Analysis
|Prague, Czech Republic
|November 7–10, 2017
|GMO detection, Next Generation sequencing, Bioinformatic
|Next Generation sequencing (NGS) is a new way to detect and characterize genetically modified organisms (GMOs). However, the technology is not always able to cover the sequence of the whole genome due to the fact that the genome size can be very different from one plant species to another and because some regions of the genome can be deeply sequenced while other are not covered. This issue is increased if the sample to analyse contains a mix of several plant species. The strategy proposed here is an enrichment of the regions of interest prior to sequencing. These sequences of interest are structural elements that can be met in transgenic constructs. In this work, the sequences of 10 promoters, 6 terminators and 20 genes present in GM constructs were used to create a library of DNA sequences. Capture probes were designed to cover the sequences of the DNA library and to fish the fragments of interest. The fragments were then sequenced on Illumina Hiseq2500. Two subsequent approaches were followed: first, the detection of GMOs on the base of the assignation of the reads to the different sequences composing the DNA library and second, the evaluation of the possibilities to create contigs with the sequences obtained to characterize the GM construct. Analysis of the NGS outputs also requires some new development in bioinformatics due to the huge amount of data. Bioinformatic scripts and pipeline analysis were created to align the reads on reference genomes and the DNA library, filter the reads in function of their alignment scores and proceed to a statistical analysis of the results to determine if they can be distinguished from the noise band and be assimilated to positive results. In a second step, a pipeline to create contigs was developed. This work was realized on DNA extracted from several GM plants. After bioinformatics treatment, the targeted elements were positively detected if present. Only few of them presented problems due to the similarities with sequences that can be naturally present in some plants and were removed from the next version of the DNA library used for enrichment. Contigs can be used to characterize the GM constructs and this approach permits to determine the junction between the elements present in the transgenic construct. The quality of the results however decreases as a function of the GM percentage.
|Debode, F., Hulin, J., Charloteaux, B., Coppieters, W., Hanikenne, M., Berben, G.