The DOI matches its Crossref record; 51 of the 52 references it cites were found in a registry or an index.
Detection and Identification of Genome Editing in Plants: Challenges and Opportunities
Open accessAbstract
Conventional genetic engineering techniques generate modifications in the genome via stable integration of DNA elements which do not occur naturally in this combination. Therefore, the resulting organisms and (most) products thereof can unambiguously be identified with event-specific PCR-based methods targeting the insertion site. New breeding techniques such as genome editing diversify the toolbox to generate genetic variability in plants. Several of these techniques can introduce single nucleotide changes without integrating foreign DNA and thereby generate organisms with intended phenotypes. Consequently, such organisms and products thereof might be indistinguishable from naturally occurring or conventionally bred counterparts with established analytical tools. The modifications can entirely resemble random mutations regardless of being spontaneous or induced chemically or via irradiation. Therefore, if an identification of these organisms or products thereof is demanded, a new challenge will arise for (official) seed, food and feed testing laboratories and enforcement institutions. For detailed consideration, we distinguish between the detection of sequence alterations - regardless of their origin - the identification of the process that generated a specific modification and the identification of a genotype, i.e., an organism produced by genome editing carrying a specific genetic alteration in a known background. This article briefly reviews the existing and upcoming detection and identification strategies (including the use of bioinformatics and statistical approaches) in particular for plants developed with genome editing techniques.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Figures
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“SDN-2 and SDN-3 rely on homology-directed repair (HDR) in which a template DNA sequence is used (Grohmann et al., 2019).”
From Genetic resources and precise gene editing for targeted improvement of barley abiotic stress tolerance (2023) · cites this paper as Grohmann et al., 2019
In the citing paper
“SDN-1 products rely on a non-homologous end joining (NHEJ) pathway to introduce a few base insertions or deletions.”
From Genetic resources and precise gene editing for targeted improvement of barley abiotic stress tolerance (2023) · cites this paper as Grohmann et al., 2019
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Basic local alignment search tool
Altschul, S. F., Gish, W., Miller, W., Myers, E. W., & Lipman, D. J. (1990) · Journal of Molecular Biology · doi:10.1006/jmbi.1990.9999 · Cited by 98,669
Development and Applications of CRISPR-Cas9 for Genome Engineering
Hsu, P. D., Lander, E. S., & Zhang, F. (2014) · Cell · doi:10.1016/j.cell.2014.05.010 · Cited by 5,762
Wang, Y., Cheng, X., Shan, Q., Zhang, Y., Liu, J., Gao, C., & Qiu, J.-L. (2014) · Nature Biotechnology · doi:10.1038/nbt.2969 · Cited by 2,072
The CRISPR/Cas9 system for plant genome editing and beyond
Bortesi, L., & Fischer, R. (2014) · Biotechnology Advances · doi:10.1016/j.biotechadv.2014.12.006 · Cited by 1,289
DNA-free genome editing in plants with preassembled CRISPR-Cas9 ribonucleoproteins
Woo, J. W., Kim, J., Kwon, S. I., Corvalán, C., Cho, S. W., Kim, H., Kim, S.-G., Kim, S.-T., Choe, S., & Kim, J.-S. (2015) · Nature Biotechnology · doi:10.1038/nbt.3389 · Cited by 1,219
The Rate and Molecular Spectrum of Spontaneous Mutations in Arabidopsis thaliana
Ossowski, S., Schneeberger, K., Lucas‐Lledó, J. I., Warthmann, N., Clark, R. M., Shaw, R. G., Weigel, D., & Lynch, M. (2009) · Science · doi:10.1126/science.1180677 · Cited by 1,166
Zhang, Y., Liang, Z., Zong, Y., Wang, Y., Liu, J., Chen, K., Qiu, J., & Gao, C. (2016) · Nature Communications · doi:10.1038/ncomms12617 · Cited by 927
Zhang, H., Zhang, J., Wei, P., Zhang, B., Gou, F., Feng, Z., Mao, Y., Yang, L., Zhang, H., Xu, N., et al. (2014) · Plant Biotechnology Journal · doi:10.1111/pbi.12200 · Cited by 799
Svitashev, S. K., Young, J. K., Schwartz, C., Gao, H., Falco, S. C., & Cigan, A. M. (2015) · PLANT PHYSIOLOGY · doi:10.1104/pp.15.00793 · Cited by 758
Fauser, F., Schiml, S., & Puchta, H. (2014) · The Plant Journal · doi:10.1111/tpj.12554 · Cited by 733
Cited by
Sorted by citations
Role of New Plant Breeding Technologies for Food Security and Sustainable Agricultural Development
Qaim, M. (2020) · Applied Economic Perspectives and Policy · doi:10.1002/aepp.13044 · Cited by 594
Genome Edited Crops Touch the Market: A View on the Global Development and Regulatory Environment
Menz, J., Modrzejewski, D., Hartung, F., Wilhelm, R., & Sprink, T. (2020) · Frontiers in Plant Science · doi:10.3389/fpls.2020.586027 · Cited by 275
Self-citationEntine, J., Felipe, M. S. S., Groenewald, J., Kershen, D. L., Lema, M. A., McHughen, A., Nepomuceno, A. L., Ohsawa, R., Ordonio, R. L., Parrott, W. A., et al. (2021) · Transgenic Research · doi:10.1007/s11248-021-00257-8 · Cited by 191
Genome editing around the globe: An update on policies and perceptions
Sprink, T., Wilhelm, R., & Hartung, F. (2022) · PLANT PHYSIOLOGY · doi:10.1093/plphys/kiac359 · Cited by 105
Self-citationCRISPR-Based Genome Editing Tools: Insights into Technological Breakthroughs and Future Challenges
Mushtaq, M., Dar, A. A., Skalický, M., Tyagi, A., Bhagat, N., Basu, U., Bhat, B. A., Zaid, A., Ali, S., Dar, T. U. H., et al. (2021) · Genes · doi:10.3390/genes12060797 · Cited by 100
Metadata
- Authors
- Grohmann, L., Keilwagen, J., Duensing, N., Dagand, E., Hartung, F., Wilhelm, R., Bendiek, J., & Sprink, T.
- Affiliations
- Federal Office of Consumer Protection and Food Safety (DE)
- Julius Kühn-Institut (DE)
- Corresponding author
- Grohmann, Lutz
- Venue
- Frontiers in Plant Science
- Publisher
- Frontiers Media SA
- Published
- 2019-03-12
- Volume
- 10
- Pages
- 236-236
- ISSN
- 1664-462X (ISSN-L)
- PMC
- PMC6423494
- OpenAlex
- W2922011937
- Cited by
- 135
- References
- 51
- Citations by year
- 2026: 11 · 2025: 24 · 2024: 14 · 2023: 19 · 2022: 22 · 2021: 20 · 2020: 17 · 2019: 8
- FWCI
- 12.35
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Frontiers in Plant Science (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- OpenAgrar (submittedVersion, cc-by)
- Topics
- Life Sciences › Agricultural and Biological Sciences › Plant Science › Genetically Modified Organisms Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › CRISPR and Genetic Engineering
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Identification and Quantification in Food
- Keywords
- genome editing, plants, GMO detection, bioinformatics, statistical approach, regulatory enforcement
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
