Abstract

Although the advent of several new breeding techniques (NBTs) is revolutionizing agricultural production processes, technical information necessary for their regulation is yet to be provided. Here, we show that high-throughput DNA sequencing is effective for the detection of unintended remaining foreign DNA segments in genome-edited rice. A simple k-mer detection method is presented and validated through a series of computer simulations and real data analyses. The data show that a short foreign DNA segment of 20 nucleotides can be detected and the probability that the segment is overlooked is 10−3 or less if the average sequencing depth is 30 or more, while the number of false hits is less than 1 on average. This method was applied to real sequencing data, and the presence and absence of an external DNA segment were successfully proven. Additionally, our in-depth analyses also identified some weaknesses in current DNA sequencing technologies. Hence, for a rigorous safety assessment, the combination of k-mer detection and another method, such as Southern blot assay, is recommended. The results presented in this study will lay the foundation for the regulation of NBT products, where foreign DNA is utilized during their generation.

Details

Title
Foreign DNA detection by high-throughput sequencing to regulate genome-edited agricultural products
Author
Itoh Takeshi 1   VIAFID ORCID Logo  ; Onuki Ritsuko 2 ; Tsuda Mai 3 ; Oshima Masao 4 ; Endo Masaki 5   VIAFID ORCID Logo  ; Sakai Hiroaki 1 ; Tanaka, Tsuyoshi 6 ; Ohsawa Ryo 3 ; Tabei Yutaka 5 

 National Agriculture and Food Research Organization, Bioinformatics Team, Advanced Analysis Center, Tsukuba, Japan (GRID:grid.416835.d) (ISNI:0000 0001 2222 0432); National Institute of Agrobiological Sciences, Tsukuba, Japan (GRID:grid.410590.9) (ISNI:0000 0001 0699 0373) 
 National Agriculture and Food Research Organization, Bioinformatics Team, Advanced Analysis Center, Tsukuba, Japan (GRID:grid.416835.d) (ISNI:0000 0001 2222 0432); National Institute of Agrobiological Sciences, Tsukuba, Japan (GRID:grid.410590.9) (ISNI:0000 0001 0699 0373); National Cancer Center Japan, Research Institute, Chuo-ku, Japan (GRID:grid.272242.3) (ISNI:0000 0001 2168 5385) 
 University of Tsukuba, Tsukuba Plant Innovation Research Center, Tsukuba, Japan (GRID:grid.20515.33) (ISNI:0000 0001 2369 4728) 
 National Institute of Agrobiological Sciences, Tsukuba, Japan (GRID:grid.410590.9) (ISNI:0000 0001 0699 0373); University of Tsukuba, Tsukuba Plant Innovation Research Center, Tsukuba, Japan (GRID:grid.20515.33) (ISNI:0000 0001 2369 4728) 
 National Institute of Agrobiological Sciences, Tsukuba, Japan (GRID:grid.410590.9) (ISNI:0000 0001 0699 0373); National Agriculture and Food Research Organization, Institute of Agrobiological Sciences, Tsukuba, Japan (GRID:grid.416835.d) (ISNI:0000 0001 2222 0432) 
 National Agriculture and Food Research Organization, Bioinformatics Team, Advanced Analysis Center, Tsukuba, Japan (GRID:grid.416835.d) (ISNI:0000 0001 2222 0432); National Agriculture and Food Research Organization, Institute of Crop Science, Tsukuba, Japan (GRID:grid.416835.d) (ISNI:0000 0001 2222 0432) 
Publication year
2020
Publication date
2020
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2378835336
Copyright
This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.