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100 ‘Genetic Zipper’ Technology-Based Oligonucleotide Insecticides Generated in 15 Minutes Using DNAInsector Algorithm (dnainsector.com): Fast and Potent Tool for Pest Control

Submitted:

20 September 2025

Posted:

22 September 2025

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Abstract
The article provides basic knowledge on how to calculate selectivity of oligonucleotide pesticides when ‘genetic zipper’ (‘GZ’) technology is used to provide safety for non-target organisms. Also here we represent 100 ‘GZ’ technology-based oligonucleotide insecticides generated in 15 minutes using DNAInsector algorithm (dnainsector.com) to show that ‘GZ’ technology is amazing approach transferring us to a new oligo era of development of potent and selective oligonucleotide pesticides based on new principles prompted by nature.
Keywords: 
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Introduction

Today, in plant protection, there is an understanding that it is necessary to create genus- and species-specific pesticides that could solve problems with globally important pests being safe for non-target organisms [1]. Oligonucleotide pesticides based on ‘genetic zipper’ (‘GZ’) technology have an easily adaptable structure and a selective DNA containment mechanism of action, which opens up the possibility of effective and well-tailored pest control with minimal side effects [2,3]. Oligonucleotide pesticides can be designed very quickly using DNAInsector program (available at dnainsector.com) or manually, based on pre-rRNA and mature rRNA sequences retrieved from the GenBank database [4]. In practical terms, this means that individuals with basic sequence knowledge can quickly design an oligonucleotide pesticide complementary to the pre-rRNA or mature rRNA of a susceptible to this approach pest with a high probability of success. In this article we represent 100 ‘GZ’ technology-based oligonucleotide insecticides generated in 15 minutes using DNAInsector algorithm (dnainsector.com) to show that ‘GZ’ technology is amazing approach transferring us to a new oligo era of development of potent and selective oligonucleotide pesticides based on new principles prompted by nature (Table 1). Already today, the ‘GZ’ technology is potentially capable of controlling 20% of all invertebrate pests with a simple and flexible algorithm [3]. However, to ensure species specificity, it is essential to compare homologous target sites of pre-rRNA and mature rRNA in non-target organisms to prevent off-target effects [3,4].

How to Calculate Selectivity of Oligonucleotide Pesticides?

A very important preoperative recommendation is how to calculate the safety of a specific oligonucleotide pesticide in an ecosystem for a range of non-target organisms [4]. To do this, select a target rRNA region (for example, 500 nt long fragment of 28S rRNA) of a pest and corresponding regions of non-target organisms. This requires knowing, after DNA sequencing, the target rRNA sequence (in our case it is 500 nt long fragment of 28S rRNA) of all invertebrates of a given ecosystem (other animals and plants will not be susceptible to ‘GZ’ technology due to physiological barriers). Next, align target 500 nt long fragment of 28S rRNA of all invertebrates of a given ecosystem, select the most differing part of the sequence that belongs to pest (it can be ~100 nt long sequence out of 500 nt long fragment of 28S rRNA), and then upload it to the DNAInsector web tool. Generate unique oligonucleotide pesticide 11 nt long and check one more time, adjust manually if required, that it is not complementary elsewhere to the target 500 nt long fragment of 28S rRNA of non-target invertebrates. Mathematically, with a high probability (>99.9%), this oligonucleotide pesticide will also not be complementary to other rRNAs of non-target invertebrates in a given ecosystem. Therefore, information on total rRNA (which includes 5S, 5.8S, 12S, 16S, 18S, 28S, ETS and ITS regions and comprising ca. 10,000 nt in each non-target invertebrate) is not required, what significantly simplifies the selection of potent and selective oligonucleotide pesticides [4].
Beginning from 2008, in our research work we found that pre-rRNA and mature rRNA is a convenient target for oligonucleotide pesticides, while mRNA, due to much lower concentration, will be much less susceptible to them, even if oligonucleotide pesticides will possess perfect complementarity to it. Pest rRNA comprises 80-85% of all RNA in the cell [5] and its use as a target for ‘GZ’ technology helps making this approach very efficient and selective at the same time [2,4]. Thousands of different mRNAs make up only 5% of all RNA and use of mature rRNA and pre-rRNA for targeting substantially increases signal-to-noise ratio, ca. 105:1 (rRNA vs. random mRNA) [6].
Importantly, for ‘GZ’ technology it would be easy to create algorithms (plans) of designing potent and selective oligonucleotide pesticides for other cases, such as when an ecosystem contains two major pests and a dozen non-target organisms or when one species is pest and closely related species is beneficial, and many other scenarios of pest control [4]. The algorithm of ‘GZ’ technology is very simple and efficient, fundamentally different from all modern approaches to plant protection, including RNAi and CRISPR/Cas [3]. In a sense, ‘GZ’ technology is an oligo universe for the scientific exploration by a biologist or a plant protection specialist. And if they enter this oligo universe, it will enrich their capabilities.

Author Contributions

Conceptualization, V.O.; methodology, K.L., O.A., A.D., A.S., N.S. and N.G.; software, N.G.; validation, V.O.; formal analysis, V.O. and N.G.; investigation, V.O., K.L., O.A., A.D., A.S., N.S. and N.G.; resources, V.O.; data curation, V.O.; writing—original draft preparation, V.O. and N.G.; writing—review and editing, V.O. and N.G.; project administration, V.O.; funding acquisition, V.O. All authors have read and agreed to the published version of the manuscript.

Funding

The research obtained funding from the Russian Science Foundation No. 25-16-20070, https://rscf.ru/project/25-16-20070/ (accessed on 19 September 2025).

Data Availability Statement

The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding authors.

Acknowledgments

We thank our many colleagues, too numerous to name, for the technical advances and lively discussions that have prompted us to write this article. We apologize to the many colleagues whose work has not been cited. Research work was carried out at the Molecular Genetics and Biotechnologies Lab created within the framework of a state assignment V.I. Vernadsky Crimean Federal University for 2024 and the planning period of 2024–2026 No. FZEG-2024–0001. We are very much indebted to all anonymous reviewers and our colleagues from the Lab for DNA technologies, PCR analysis, and the creation of DNA insecticides (V.I. Vernadsky Crimean Federal University, Institute of Biochemical Technologies, Ecology and Pharmacy, Department of General Biology and Genetics), and OLINSCIDE BIOTECH LLC. for the valuable comments on our manuscript.

Conflicts of Interest

The authors declare no conflicts of interest.

References

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Table 1. 100 ‘genetic zipper’ technology-based oligonucleotide insecticides generated in 15 minutes using DNAInsector algorithm (dnainsector.com).
Table 1. 100 ‘genetic zipper’ technology-based oligonucleotide insecticides generated in 15 minutes using DNAInsector algorithm (dnainsector.com).
Reference Latin name GenBank ID Target rRNA Sequence of oligonucleotide insecticide
(5’..3’)
1 10.1603/008.103.0105 Abgrallaspis aguacatae GQ478401.1 28S TGTTAGACTCC
2 10.1080/095831500750016389 Abgrallaspis cyanophylli JQ651301.1 28S CACCATCTTCC
3 10.1111/j.1440-6055.1976.tb01714.x Acizzia dodonaeae MG195297.1 18S CTAATAAAAGC
4 10.1371/journal.pone.0214220 Acizzia errabunda MG195288.1 18S CTAGAATTACC
5 10.13140/RG.2.2.22942.72008 Acizzia sasakii MK039563.1 16S ATTTCTCTTCC
6 10.1093/jisesa/ieae032. Acutaspis scutiformis KY219127.1 28S TTCATTACGCC
7 10.1371/journal.pone.0251663 Adelges laricis AF275215.1 12S AATAAAATACC
8 10.1111/syen.12033 Affirmaspis cederbergensis MH934019.1 28S CCATCTTCCCC
9 10.1111/epp.12760. Aleurocanthus camelliae OQ180914.1 16S TTTACTGCAGC
10 10.3390/insects11010042 Aleurocanthus spiniferus OQ180915.1 16S TAATTTACTGC
11 10.1080/21658005.2013.795042 Aleurochiton aceris AY521267.1 16S ATTGTTGTACC
12 10.61310/mndjstea.1015.23 Aleurodicus dispersus JQ305695.1 16S TTTCATTGAGC
13 10.1016/S0305-0491(99)00054-1 Aleurodicus dugesii U06474.1 18S TTAGAACTAGG
14 10.3956/2010-05.1 Aleuroplatus coronata EU441164.1 16S TGTTAAACAGG
15 10.3956/2010-05.1 Aleuroplatus gelatinosus EU441163.1 16S AAATTTAAGCC
16 10.1079/cabicompendium.4538 Aleurothrixus floccosus HG810135.1 16S TCTGTTCGACC
17 10.1093/jisesa/ieu136 Aleurotrachelus camelliae OQ180920.1 28S TTATTACAACC
18 10.1007/s41348-020-00319-9 Aleyrodes proletella MW644572.1 16S ATTTACTGCGG
19 http://dx.doi.org/10.3733/ca.v054n06p26 Aphis gossypii HG810150.1 16S TAAATATTAGG
20 10.12681/eh.13916 Anapulvinaria pistaciae OR074914.1 5.8S GTTTGTACAGC
21 10.11646/zootaxa.4117.1.4 Ancepaspis edentata KY220051.1 28S ACCTACTGTCC
22 10.21608/sjas.2024.322627.1461 Aonidiella pini MK886648.1 28S ATCAAACAACC
23 10.1080/00222939100770791 Aphalaroida inermis MG988580.1 18S CACAGTTATCC
24 10.1080/00779962.2007.9722151 Arytainilla spartiophila MG988581.1 18S AACCCTAATCC
25 10.3897/zookeys.867.34937 Aspidaspis florenciae KY219598.1 28S ACCATCTTCCC
26 10.1079/cabicompendium.7490 Aspidiella hartii KY219906.1 28S TCCTGAATACC
27 10.1079/cabicompendium.7506 Aspidiella sacchari DQ145368.2 28S TCCCGTTTACC
28 10.1079/cabicompendium.7415 Aspidiotus destructor DQ145293.2 28S CATAGTTCACC
29 10.3897/zookeys.1047.68409. Aspidiotus fularum MH934073.1 28S TTTCATTACGC
30 10.1603/AN10060 Aspidiotus nerii DQ145297.2 28S TTCATCCTGGC
31 10.1016/j.aspen.2020.02.002 Aspidiotus rigidus OL437057.1 28S TCTTTCGCCCC
32 10.3897/zookeys.1174.105851 Aulacaspis difficilis DQ145298.2 28S ATATCAAACGG
33 10.3897/zookeys.1174.105851 Aulacaspis distylii DQ145299.2 28S AGTCTTTCGCC
34 10.1111/epp.12778 Aulacaspis rosae KY219387.1 28S GCTTACTGTCC
35 10.1016/S1226-8615(08)60379-9 Aulacaspis spinosa DQ145367.2 28S GCAATTCCTCC
36 10.11646/zootaxa.4272.1.6 Austrolecanium cryptocaryae KY816393.1 18S TTTAATGAGCC
37 10.11646/zootaxa.4272.1.6 Austrolecanium sassafras KY816397.1 18S CAAGTCTTTGC
38 10.11646/zootaxa.4508.1.6 Austrolichtensia hakearum MH844461.1 18S TTTCACCGTGC
39 10.1007/978-3-030-28683-5_8 Bemisia afer GQ867747.1 16S AATCATTGAGC
40 10.1093/jee/99.3.691 Bemisia argentifolii AY521257.1 28S TTTGTATCAGG
41 10.1007/s13205-021-02831-7 Bemisia breyniae GQ867745.1 16S TGTCATTGAGC
42 10.1038/s41598-017-00528-7 Bemisia emiliae GQ867744.1 16S ATTCATTGAGC
43 10.1007/s13205-021-02831-7 Bemisia euphorbiae GQ867743.1 16S ATTATGCTACC
44 10.1007/s10340-020-01210-0 Bemisia tabaci AF110722.3 16S ATTTATTACGC
45 10.1007/s10886-012-0121-y Brachycaudus helichrysi JX965980.1 12S ACTAAAATACC
46 10.11646/zootaxa.4362.1.4 Cacopsylla
bidens
MK039580.1 16S TCATACAAGCC
47 10.3897/BDJ.10.e85094 Cacopsylla burckhardti MK039571.1 16S ATAAAACACGC
48 10.11646/zootaxa.4362.1.4 Cacopsylla chinensis LC513963.1 16S TCTTATCGTCC
49 10.1080/23802359.2021.1875908 Cacopsylla citrisuga MH053225.1 16S ACTATCACCCC
50 10.1186/s12866-020-01895-4 Cacopsylla heterogena MH053234.1 16S AAAAATTATGC
51 10.11646/zootaxa.4362.1.4 Cacopsylla jukyungi LC513968.1 16S AATTCTATAGG
52 10.5281/zenodo.14578 Cacopsylla mali AF367822.1 12S GATAAAATACC
53 10.5281/zenodo.14578 Cacopsylla peregrina MT038953.1 28S TGCTTAAATCC
54 10.34101/actaagrar/74/1660 Cacopsylla pruni DQ778635.1 18S GTACTCATTCC
55 10.5281/zenodo.5806004 Cacopsylla pulchra MT038955.1 28S TATTAATATGC
56 10.3390/agronomy14040668. Cacopsylla pyri MK039584.1 16S AAATTATAAGG
57 10.11646/zootaxa.4362.1.4 Cacopsylla pyricola MK039589.1 16S TCTGTTCAACC
58 10.11646/zootaxa.4362.1.4 Cacopsylla pyrisuga AB721006.1 16S ACATTTTCCCC
59 10.5281/zenodo.14578 Cacopsylla ulmi MT038960.1 28S TTAAATCCACC
60 10.61310/mjst.v23i1.2370 Ceroplastes floridensis JQ795604.1 28S TCCTGAATTCC
61 10.1007/s13744-016-0480-0 Ceroplastes glomeratus KX670822.1 28S TTCAACTTTCC
62 10.11646/zootaxa.4701.6.2 Ceroplastes kunmingensis MT316993.1 28S CTTCATCCTGG
63 10.11646/zootaxa.4701.6.2 Ceroplastes murrayi MT316994.1 28S ACTTTCATTGC
64 https://doi.org/10.1079/pwkb.species.12351
https://doi.org/10.2903/j.efsa.2024.8888
Ceroplastes rubens MT317009.1 28S TTCATTGCGCC
65 10.11609/jott.7419.14.2.20606-20614 Ceroplastes rusci PV762166.1 28S CATCTTCCCCC
66 10.1079/cabicompendium.12353 Ceroplastes sinensis KY085826.1 28S GTCCGTTTACC
67 10.1079/cabicompendium.120372 Ceroplastes stellifer MK533217.1 28S TCCGTTTACCC
68 10.5281/zenodo.14578 Chamaepsylla hartigii MT038961.1 5.8S TAATCTTGCCC
69 10.1111/j.1095-8312.2011.01716.x Chionaspis americana KY220045.1 28S TTGAATTCCGC
70 10.1111/epp.12287 Chionaspis etrusca DQ145397.2 28S GATCGATTTGC
71 10.1590/S1519-566X2010000300013 Coccus alpinus JX499976.1 28S AAATTCATCGC
72 10.1079/cabicompendium.14663 Coccus celatus MT317016.1 28S AACTGAATTCC
73 10.3897/zookeys.734.22774 Coccus ficicola MK533218.1 28S TTACTCCTCGG
74 10.3897/zookeys.244.4045 Coccus formicarii MZ782004.1 28S CCTCGATTACC
75 10.1017/S0007485300010919 Coccus longulus MT317024.1 28S TGACTTCATCC
76 10.11646/zootaxa.3646.2.2 Cornopsylla rotundiconis MH758086.1 28S TGCCCTTTTGC
77 10.11646/zootaxa.4508.1.6 Cryptes baccatus MZ782005.1 28S TATATCGTCGG
78 10.11646/zootaxa.4508.1.6 Cryptes utzoni MH886632.1 28S GTTTCGTTCGC
79 10.1111/jen.12937 Diaphorina communis MH042733.1 16S GCTGTTATCCC
80 10.1080/23802359.2021.1906175 Didesmococcus koreanus MH844459.1 18S CATGTATTAGC
81 10.1093/gigascience/giz113 Ericerus pela KX380986.1 18S CCAATTGATCC
82 10.1093/jipm/pmv016 Eriopeltis festucae MT317080.1 28S CCATCTTTCGG
83 10.1042/bj0660289 Eucallipterus tiliae KX631489.1 16S CATTCTAGTCC
84 10.1603/0022-0493-98.4.1202 Eulecanium cerasorum MK533231.1 28S TAGTCTTTCGC
85 https://doi.org/37.10.5281/zenodo.5806004. Livilla horvathi AF367826.1 12S CTTTTAAATCC
86 http://dx.doi.org/10.5252/z2015n1a13 Livilla pyrenaea AF367832.1 12S TTAATAATTCC
87 10.4289/0013-8797.119.1.162 Livilla variegata AF367837.1 12S ATCCTATTTCC
88 10.1093/jee/toae041 Myzus cerasi KX631445.1 16S CATACAAGTCC
89 10.1007/s12600-023-01059-w Paraleyrodes bondari GQ867760.1 16S TCTCATTGAGC
90 10.1093/jisesa/ieu136 Pealius mori HG810145.1 16S TTGGATTAAGC
91 10.5656/KSAE.2012.04.1.83 Pealius rhododendri GQ867752.1 16S GTTCATTGAGC
92 10.13140/RG.2.2.14711.39848 Psylla alni MG988605.1 18S ACTTTGCTTGC
93 10.13140/RG.2.2.14711.39848 Psylla alniformosanaesuga MH758107.1 28S GGTATTTCACC
94 10.1111/epp.12636 Psylla buxi MG988606.1 18S CTTTTACTTCC
95 https://doi.org/37.10.5281/zenodo.5806004. Psylla foersteri MG988583.1 18S AATACGAATGC
96 10.1673/031.010.12001 Siphoninus phillyreae Z15053.1 18S GTTAGCTTTGG
97 10.3897/travaux.66.e98619 Spanioneura fonscolombii MG988609.1 18S ATCAAGTTTGG
98 10.5958/0974-8172.2018.00158.X Tetraleurodes acaciae ON311124.1 18S CCTATAAAAGG
99 10.1111/j.1365-2311.2004.00586.x Tetraleurodes mori AY521263.1 16S TTAGTTAATGG
100 10.1038/s41598-024-84958-0 Trialeurodes ricini HG810146.1 16S ATAAGATTAGG
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