[en] Next generation sequencing (NGS) is a promising tool for analysing the quality and safety of food and feed products. The detection and identification of genetically modified organisms (GMOs) is complex, as the diversity of transgenic events and types of structural elements introduced in plants continue to increase. In this paper, we show how a strategy that combines enrichment technologies with NGS can be used to detect a large panel of structural elements and partially or completely reconstruct the new sequence inserted into the plant genome in a single analysis, even at low GMO percentages. The strategy of enriching sequences of interest makes the approach applicable even to mixed products, which was not possible before due to insufficient coverage of the different genomes present. This approach is also the first step towards a more complete characterisation of agrifood products in a single analysis.
Disciplines :
Agriculture & agronomy
Author, co-author :
Debode, Frederic
Hulin, Julie
CHARLOTEAUX, Benoit ; Centre Hospitalier Universitaire de Liège - CHU > Unilab > Service de génétique
Coppieters, Wouter ; Université de Liège - ULiège > Dpt. de gestion vétérinaire des Ressources Animales (DRA) > Génomique animale
Hanikenne, Marc ; Université de Liège - ULiège > Département des sciences de la vie > Génomique fonctionnelle et imagerie moléculaire végétale
Michael, T. P. & Jackson, S. The first 50 plant genomes. Plant Genome 6 (2013).
Kovalic, D. et al. The use of next generation sequencing and junction sequence analysis bioinformatics to achieve molecular characterization of crops improved through modern biotechnology. Plant Genome 5, 149–163 (2012).
Wahler, D. et al. Next-generation sequencing as a tool for detailed molecular characterisation of genomic insertions and flanking regions in genetically modified plants: a pilot study using a rice event unauthorised in the EU. Food Anal. Meth. 6, 1718–1727 (2013).
Yang, L. et al. Characterization of GM events by insert knowledge adapted re-sequencing approaches. Sci. Rep. 3 (2013).
Liang, C. et al. Detecting authorized and unauthorized genetically modified organisms containing vip3A by real-time PCR and next-generation sequencing. Anal. Bioanal. Chem. 406, 2603–2611 (2014).
Holst-Jensen, A. et al. Application of whole genome shotgun sequencing for detection and characterization of genetically modified organisms and derived products. Anal. Bioanal. Chem. 408, 4595–4614 (2016).
Willems, S. et al. Statistical framework for detection of genetically modified organisms based on Next Generation Sequencing. Food Chem. 192, 788–798 (2016).
Schmutz, J. et al. Genome sequence of the palaeopolyploid soybean. Nature 463, 178–183 (2010).
Shi, X. & Ling, H. Q. Current advances in genome sequencing of common wheat and its ancestral species. Crop J. 6, 15–21 (2018).
Tengs, T. et al. Microarray-based method for detection of unknown genetic modifications. BMC biotechnol. 7, 91 (2007).
Tengs, T. et al. Characterization of unknown genetic modifications using high throughput sequencing and computational subtraction. BMC biotechnol. 9, 87 (2009).
Tengs, T. et al. Non-prejudiced detection and characterization of genetic modifications. Food Anal. Methods 3, 120–128 (2010).
Arulandhu, A. J. et al. NGS-based amplicon sequencing approach; towards a new era in GMO screening and detection. Food Control 93, 201–210 (2018).
Fraiture, M. A. et al. Validation of a sensitive DNA walking strategy to characterise unauthorised GMOs using model food matrices mimicking common rice products. Food Chem. 173, 1259–1265 (2015).
Košir, A. B. et al. ALF: a strategy for identification of unauthorized GMOs in complex mixtures by a GW-NGS method and dedicated bioinformatics analysis. Sci. Rep. 8, 17645 (2018).
Fraiture, M. A. et al. Development and validation of an integrated DNA walking strategy to detect GMO expressing cry genes. BMC biotechnol. 18, 40 (2018).
Arulandhu, A. J. et al. DNA enrichment approaches to identify unauthorised genetically modified organisms (GMOs). Anal. Bioanal. Chem. 408, 4575–4593 (2016).
Block, A. et al. The GMOseek matrix: a decision support tool for optimizing the detection of genetically modified plants. BMC Bioinformatics 14, 256 (2013).
Debode, F. Développement de méthodologies pour la détection des plantes génétiquement modifiées. Phd Thesis, AGRO, UCL, 367/ 2017, 391 p., http://hdl.handle.net/2078.1/186329 (2017).
Angenon, G. et al. Antibiotic resistance markers for plant transformation. In Plant molecular biology manual, Springer, Dordrecht, 125–137 (1994).
Sulonen, A. M. et al. Comparison of solution-based exome capture methods for next generation sequencing. Genome Biol. 12, 94 (2011).
Teer, J. K. Systematic comparison of three genomic enrichment methods for massively parallel DNA sequencing. Genome Res. 20, 1420–1431 (2010).
Bodi, K. et al. Comparison of commercially available target enrichment methods for next-generation sequencing. J. Biomol. Tech. 24, 73 (2013).
Meienberg, J. et al. New insights into the performance of human whole-exome capture platforms. Nucleic Acids Res. 43, 1–14 (2015).
Chilamakuri, C. S. R. et al. Performance comparison of four exome capture systems for deep sequencing. BMC genomics 15, 449 (2014).
García-García, G. et al. Assessment of the latest NGS enrichment capture methods in clinical context. Sci. Rep. 6, 20948 (2016).
IUPAC Compendium of Chemical Terminology, 2nd ed. (Compiled by McNaught, A. D. & Wilkinson A.). Blackwell Scientific Publications, Oxford., 464 pages. ISBN 0-9678550-9-8 (1997).
Windels, P. et al. Characterisation of the Roundup Ready soybean insert. Eur. Food Res. Technol. 213, 107–112 (2001).
Fraiture, M. A. et al. Nanopore sequencing technology: a new route for the fast detection of unauthorized GMO. Sci. Rep. 8, 7903 (2018).
Debode, F. et al. Development of 10 new screening PCR assays for GMO detection targeting promoters (pFMV, pNOS, pSSuAra, pTA29, pUbi, pRice actin) and terminators (t35S, tE9, tOCS, tg7). Eur. Food Res. Technol. 236, 659–669 (2013).
Debode, F. et al. Development of PCR screening assays focused on gene-coding sequences for GMO detection. Biotechnol. Agron. Soc. Environ. 22, 230–241 (2018).
ISO 21571. Foodstuffs. Methods of analysis for the detection of genetically modified organisms and derived products. Nucleic acid extraction. International Organization for Standardization, Geneva (2005).
Li, H. & Durbin, R. Fast and accurate short read alignment with Burrows–Wheeler transform. Bioinformatics 25, 1754–1760 (2009).
Li, H. et al. The sequence alignment/map format and SAMtools. Bioinformatics 25, 2078–2079 (2009).
Wickham, H. ggplot2: elegant graphics for data analysis. J. Stat. Softw. 35, 65–88 (2010).
Li, H. Seqtk Toolkit for processing sequences in FASTA/Q formats, https://github.com/lh3/Seqtk (2012).
Zerbino, D. R. & Birney, E. Velvet: algorithms for de novo short read assembly using de Bruijn graphs. Genome Res. 18, 821–829 (2008).
Chevreux, B. et al. Genome Sequence Assembly Using Trace Signals and Additional Sequence Information. Computer Science and Biology. In: Proceedings of the German Conference on Bioinformatics, 45–56 (1999).
Bankevich, A. et al. SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing. J. Comput. Biol. 19, 455–477 (2012).
Lin, S. H. & Liao, Y. C. CISA: contig integrator for sequence assembly of bacterial genomes. PloS one 8, e60843 (2013).
Morgulis, A. et al. Database indexing for production MegaBLAST searches. Bioinformatics 24, 1757–1764 (2008).
Camacho, C. et al. BLAST+: architecture and applications. BMC bioinformatics 10, 421 (2009).
