Submitted:
20 September 2025
Posted:
22 September 2025
Read the latest preprint version here
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:
DNA insecticides
; oligonucleotide pesticides
; olinscides
; rRNA
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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