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Foliar application of clay-delivered RNA interference for whitefly control

Nature Plants volume 8, pages 535–548 (2022)Cite this article

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Abstract

Whitefly (Bemisia tabaci) is a phloem-feeding global agricultural pest belonging to the order Hemiptera. Foliar application of double-stranded RNA (dsRNA) represents an attractive avenue for pest control; however, limited uptake and phloem availability of the dsRNA has restricted the development of RNA interference (RNAi)-based biopesticides against sap-sucking insects. Following high-throughput single and combinational target gene identification for additive effects, we report here that foliar application of dsRNA loaded onto layered double hydroxide (LDH), termed BioClay, can effectively disrupt multiple whitefly developmental stages in planta. Adjuvants were shown to enhance uptake and movement of foliar-applied dsRNA to vascular bundles and into the whitefly. Notably, delivering the dsRNA as a BioClay spray instead of as naked dsRNA improved protection against immature insect stages, demonstrating the platform’s potential to extend the benefits offered by RNA insecticides towards complete life cycle control of whitefly and potentially other pests.

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Fig. 1: Characterization of MgFe-LDH and dsRNA-LDH (BioClay) demonstrates consistent dsRNA loading with adjuvants and uniform LDH distribution upon leaf deposition.
Fig. 2: High-throughput RNAi screening identified potential target genes in whitefly.
Fig. 3: Specific combinations of dsRNAs targeting multiple whitefly transcripts increase RNAi-mediated mortality.
Fig. 4: The addition of selected adjuvants improves uptake and internalization of foliar-applied dsRNA into cotton leaves.
Fig. 5: Following foliar application, dsRNA released from the LDH carrier is taken up and internalized by cotton leaves.
Fig. 6: Intact dsRNAs are taken up into whiteflies from diet bioassays and via leaf dip or foliar application.
Fig. 7: Foliar application of BioClay provides robust control of whitefly life cycle.
Fig. 8: Foliar-applied dsRNA-LDH (BioClay) provides safe and effective in planta protection from whitefly eggs, nymphs and adults.

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Data availability

There are no restrictions on data availability. All data supporting the findings of this research are reported in the main text, figures and Supplementary Information. The gene symbols were obtained from the FlyBase database (http://flybase.org/). The RNA-seq datasets were deposited under BioProject ID PRJNA821342. The transcript sequences were obtained from the whitefly genome database (http://www.whiteflygenomics.org/cgi-bin/bta/index.cgi). Source data are provided with this paper.

Code availability

All Python code used in our analysis is available on the GitHub public repository at https://github.com/Mitter-lab/jain_et_al_code.

References

  1. Burand, J. P. & Hunter, W. B. RNAi: future in insect management. J. Invertebr. Pathol. 112, S68–S74 (2013).

    Article  CAS  PubMed  Google Scholar 

  2. Lu, S. et al. Changes in Bemisia tabaci feeding behaviors caused directly and indirectly by cucurbit chlorotic yellows virus. Virol. J. 16, 106 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  3. Hasanuzzaman, A. M., Islam, M. N., Zhang, Y., Zhang, C. Y. & Liu, T. X. Leaf morphological characters can be a factor for intra-varietal preference of whitefly Bemisia tabaci (Hemiptera: Aleyrodidae) among eggplant varieties. PLoS ONE 11, e0153880 (2016).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  4. Boykin, L. M. et al. Global relationships of Bemisia tabaci (Hemiptera: Aleyrodidae) revealed using Bayesian analysis of mitochondrial COI DNA sequences. Mol. Phylogenet. Evol. 44, 1306–1319 (2007).

    Article  CAS  PubMed  Google Scholar 

  5. Sanahuja, G., Banakar, R., Twyman, R. M., Capell, T. & Christou, P. Bacillus thuringiensis: a century of research, development and commercial applications. Plant Biotechnol. J. 9, 283–300 (2011).

    Article  CAS  PubMed  Google Scholar 

  6. Zhao, J. H., Zhang, T., Liu, Q. Y. & Guo, H. S. Trans-kingdom RNAs and their fates in recipient cells: advances, utilization, and perspectives. Plant Commun. 2, 100167 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  7. Qiao, L. L. et al. Spray-induced gene silencing for disease control is dependent on the efficiency of pathogen RNA uptake. Plant Biotechnol. J. 19, 1756–1768 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Tenllado, F. & Diaz-Ruiz, J. R. Double-stranded RNA-mediated interference with plant virus infection. J. Virol. 75, 12288–12297 (2001).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Mitter, N. et al. Clay nanosheets for topical delivery of RNAi for sustained protection against plant viruses. Nat. Plants 3, 16207 (2017).

    Article  CAS  PubMed  Google Scholar 

  10. Wang, M. et al. Bidirectional cross-kingdom RNAi and fungal uptake of external RNAs confer plant protection. Nat. Plants 2, 16151 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. San Miguel, K. & Scott, J. G. The next generation of insecticides: dsRNA is stable as a foliar-applied insecticide. Pest Manage. Sci. 72, 801–809 (2016).

    Article  CAS  Google Scholar 

  12. Fletcher, S. J., Reeves, P. T., Hoang, B. T. & Mitter, N. A perspective on RNAi-based biopesticides. Front. Plant Sci. 11, 51 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  13. Liu, S. S. et al. Evaluation of dsRNA delivery methods for targeting macrophage migration inhibitory factor MIF in RNAi-based aphid control. J. Plant Dis. Prot. 82, 257–260 (2021).

    Google Scholar 

  14. Malik, H. J. et al. RNAi-mediated mortality of the whitefly through transgenic expression of double-stranded RNA homologous to acetylcholinesterase and ecdysone receptor in tobacco plants. Sci. Rep. 6, 38469 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Raza, A. et al. RNA interference-based approach to down regulate osmoregulators of whitefly (Bemisia tabaci): potential technology for the control of whitefly. PLoS ONE 11, e0153883 (2016).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  16. Grover, S. et al. Potential of RNA interference in the study and management of the whitefly, Bemisia tabaci. Arch. Insect Biochem. Physiol. 100, e21522 (2018).

    Article  PubMed  CAS  Google Scholar 

  17. de Andrade, E. C. & Hunter, W. B. in RNA Interference – Natural Gene-based Technology For Highly Specific Pest Control (HiSPeC) (ed Abdurakhmonov, I. Y.) 391–409 (Croatia IntechOpen, 2016).

  18. Ghosh, S. K., Hunter, W. B., Park, A. L. & Gundersen-Rindal, D. E. Double strand RNA delivery system for plant-sap-feeding insects. PLoS ONE 12, e0171861 (2017).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  19. Shukla, A. K. et al. Expression of an insecticidal fern protein in cotton protects against whitefly. Nat. Biotechnol. 34, 1046–1051 (2016).

    Article  CAS  PubMed  Google Scholar 

  20. Peng, Z. et al. Genome-wide identification and analysis of chitinase-like gene family in Bemisia tabaci (Hemiptera: Aleyrodidae). Insects 12, 254 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  21. Kim, T. H., Lundehoj, L. & Nielsen, U. G. An investigation of the phosphate removal mechanism by MgFe layered double hydroxides. Appl. Clay Sci. 189, 105521 (2020).

    Article  CAS  Google Scholar 

  22. Thakur, N. et al. Enhanced whitefly resistance in transgenic tobacco plants expressing double stranded RNA of v-ATPase A gene. PLoS ONE 9, e87235 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  23. Sun, Y. W. et al. Silencing an essential gene involved in infestation and digestion in grain aphid through plant-mediated RNA interference generates aphid-resistant wheat plants. Plant Biotechnol. J. 17, 852–854 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  24. Datta, R., Heaster, T. M., Sharick, J. T., Gillette, A. A. & Skala, M. C. Fluorescence lifetime imaging microscopy: fundamentals and advances in instrumentation, analysis, and applications. J. Biomed. Opt. 25, 1–43 (2020).

    Article  PubMed  Google Scholar 

  25. Camargo, R. A. et al. RNA interference as a gene silencing tool to control Tuta absoluta in tomato (Solanum lycopersicum). PeerJ 4, e2673 (2016).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  26. Perring, T. M., Stansly, P. A., Liu, T. X., Smith, H. A. & Andreason S. A. in Whiteflies: Biology, Ecology, and Management 73–110 (Academic Press, 2018).

  27. Kaur, R., Gupta, M., Singh, S., Joshi, N. & Sharma, A. Enhancing RNAi efficiency to decipher the functional response of potential genes in Bemisia tabaci AsiaII-1 (Gennadius) through dsRNA feeding assays. Front. Physiol. 11, 123 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  28. Nufarm, Australia. Banjo https://nufarm.com/au/product/banjo/ (2021).

  29. Nufarm, Australia. Supercharge Elite https://nufarm.com/au/product/supercharge-elite/ (2021).

  30. Dubovik, V., Dalinova, A. & Berestetskiy, A. Effect of adjuvants on herbicidal activity and selectivity of three phytotoxins produced by the fungus, Stagonospora cirsii. Plants 9, 1621 (2020).

    Article  CAS  PubMed Central  Google Scholar 

  31. Miller, S. C., Miyata, K., Brown, S. J. & Tomoyasu, Y. Dissecting systemic RNA interference in the red flour beetle Tribolium castaneum: parameters affecting the efficiency of RNAi. PLoS ONE 7, e47431 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Chandra, G. S., Asokan, R., Manamohan, M. & Kumar, N. K. Enhancing RNAi by using concatemerized double-stranded RNA. Pest Manage. Sci. 75, 506–514 (2019).

    Article  CAS  Google Scholar 

  33. Dalakouras, A. et al. Induction of silencing in plants by high-pressure spraying of in vitro-synthesized small RNAs. Front. Plant Sci. 7, 1327 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  34. Huang, S., Iandolino, A. & Peel, G. Methods and compositions for introducing nucleic acids into plants. US patent 20180163219A1 (2018).

  35. Biedenkopf, D. et al. Systemic spreading of exogenous applied RNA biopesticides in the crop plant Hordeum vulgare. ExRNA 2, 12 (2020).

    Article  Google Scholar 

  36. Hunter, W. B. & Wintermantel, W. M. Optimizing efficient RNAi-mediated control of hemipteran pests (psyllids, leafhoppers, whitefly): modified pyrimidines in dsRNA triggers. Plants 10, 1782 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Linyu, W., Lianjun, Z., Ning, L., Xiwu, G. & Xiaoning, L. Effect of RNAi targeting CYP6CY3 on the growth, development and insecticide susceptibility of Aphis gossypii by using nanocarrier-based transdermal dsRNA delivery system. Pestic. Biochem. Physiol. 177, 104878 (2021).

    Article  PubMed  CAS  Google Scholar 

  38. Yan, S., Ren, B. Y. & Shen, J. Nanoparticle-mediated double-stranded RNA delivery system: a promising approach for sustainable pest management. Insect Sci. 28, 21–34 (2021).

    Article  CAS  PubMed  Google Scholar 

  39. Yong, J. et al. Sheet-like clay nanoparticles deliver RNA into developing pollen to efficiently silence a target gene. Plant Physiol. 187, 886–899 (2021).

    Article  CAS  PubMed  Google Scholar 

  40. Ma, Z. et al. Visualization of the process of a nanocarrier-mediated gene delivery: stabilization, endocytosis and endosomal escape of genes for intracellular spreading. J. Nanobiotechnology 20, 124 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Bray, N. L., Pimentel, H., Melsted, P. & Pachter, L. Near-optimal probabilistic RNA-seq quantification. Nat. Biotechnol. 34, 525–527 (2016).

    Article  CAS  PubMed  Google Scholar 

  42. Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 550 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  43. Larsson, J. eulerr: Area-Proportional Euler and Venn Diagrams with Ellipses. R package version 6.1.1 https://CRAN.R-project.org/package=eulerr (2021).

  44. Patro, R., Mount, S. M. & Kingsford, C. Sailfish enables alignment-free isoform quantification from RNA-seq reads using lightweight algorithms. Nat. Biotechnol. 32, 462–464 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Marcais, G. & Kingsford, C. A fast, lock-free approach for efficient parallel counting of occurrences of k-mers. Bioinformatics 27, 764–770 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Untergasser, A. et al. Primer3—new capabilities and interfaces. Nucleic Acids Res. 40, e115 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Supek, F., Bosnjak, M., Skunca, N. & Smuc, T. REVIGO summarizes and visualizes long lists of gene ontology terms. PLoS ONE 6, e21800 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Pfaffl, M. W. A new mathematical model for relative quantification in real-time RT-PCR. Nucleic Acids Res. 29, e45 (2001).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

This work was supported by the Horticulture Innovation Australia grant, with the Cotton Research and Development Corporation (CRDC) and Nufarm Ltd Australia (VG16037) awarded to N.M. We thank M. Pointon, B. Taylor and K. Murphy from Nufarm Australia Ltd as the industry partner; D. Barkauskas for technical assistance with confocal microscopy; G. Walter and J. Hereward for helping with stingless bee experiments; the Institute for Molecular Bioscience Microscopy facility, the Queensland node of the Australian National Fabrication Facility, and the Microscopy Australia Facility at the Centre for Microscopy and Microanalysis (CMM) of the University of Queensland for the facilities, and the scientific and technical assistance; and the Ecosciences Precinct, Department of Agriculture and Fisheries (DAF), Brisbane for providing insectary facilities. This work was supported by a Horticulture Innovation Australia grant, with the Cotton Research and Development Corporation and Nufarm Ltd Australia (grant no. VG16037) to N.M. and Z.P.X., and Advance Queensland Research Fellowship from the Queensland State Government, Australia to K.E.R. C.A.B was supported by the Australian Research Council Research Hub for Sustainable Crop Protection (project number IH190100022) and funded by the Australian Government.

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Authors and Affiliations

  1. Queensland Alliance for Agriculture and Food Innovation, Centre for Horticultural Science, The University of Queensland, St Lucia, Queensland, Australia

    Ritesh G. Jain, Stephen J. Fletcher, Narelle Manzie, Karl E. Robinson, Elvin Lu, Christopher A. Brosnan & Neena Mitter

  2. Australian Institute for Bioengineering and Nanotechnology, The University of Queensland, St Lucia, Queensland, Australia

    Peng Li & Zhi Ping Xu

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Contributions

N. Mitter and Z.P.X. conceived the project. N. Mitter conceptualized and supervised the research. R.G.J. designed and performed the experiments and analysed the data. S.J.F. performed bioinformatics analyses. P.L. carried out experiments on LDH synthesis and characterization. E.L. conducted plants-based insectary trials. R.G.J., S.F. and N. Mitter wrote the paper. N. Manzie and K.E.R. discussed the results and commented on the manuscript. C.A.B. participated and contributed to the revision of the manuscript. All authors reviewed and approved the manuscript before submission.

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Correspondence to Neena Mitter.

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Extended data

Extended Data Fig. 1 Characterization of MgFe-LDH and BioClay, and confirmation of a uniform layer of LDH is formed that mirrors the leaf surface.

a, X-ray diffraction (XRD) pattern of LDH showing the typical basal peaks of (003) and (006) lattices, which is in accordance with JCPDS 70-2150, and therefore confirms the expected LDH structure. b, Transmission Electron Microscopy (TEM) image of LDH showed the typical agglomeration of these particles. The lateral sizes of single-piece LDH crystals were 20-40 nm. c, Dynamic light scattering (DLS) illustrates the particle size distribution of LDH and BioClay in suspension. LDH aggregates have a micrometer-level size similar to that of BioClay, confirming that the addition of dsRNA has a minimal effect on the size factor. d, SEM images (UVD mode) of LDH confirm deposition on the leaf surface at low magnification matched that of the negative control leaf, suggesting a flat, even distribution of LDH on the leaf surface. e, At high magnification, uniform LDH deposition with minor cracks was evident at two hours. On day 14, reduced thickness of LDH residue and notable cracks were observed, indicating consumption of LDH over time. Rigorous washing of leaves two hours post-spray application did not affect the LDH coverage compared to the unwashed leaf. However, rigorous washing on day 14 changed the LDH deposition due to reduced fastness caused by the consumption of LDH. The formation changes of LDH deposition after washing are proposed to depend on the initial amount sprayed. These SEM images adopt a common UVD signal and have the same visual fields as Figs. 1d and e, respectively. Scale bar = 50 μm and 500 μm.

Source data

Extended Data Fig. 2 Scanning electron microscopy (SEM) images of dsRNA-LDH (BioClay) show uniform BioClay distribution upon leaf deposition.

a-d, SEM images of Syntaxin dsRNA-LDH deposition on the adaxial (upper) surface of a cotton leaf (a,c) around stomata (b,d). The images adopted signals in backscattered electron (BSE) mode that can visualize the contrast of materials. In this mode, the BioClay deposition pattern on the leaf surface became visible (indicated by yellow arrows), which is not distinguished in the common UVD signal mode. The images after 2 h (ii and iii) and 14 days (iv and v) from treatment, with (iii and v) and without (ii and iv) washing, illustrated the uniform distribution of BioClay on the leaf surface, as well as the consumption and the fastness of BioClay. Scale bar = 50 μm and 500 μm.

Extended Data Fig. 3 Differential cotton transcript expression in leaf tissue following foliar application does not reveal stress-related perturbation in response to LDH.

Heatmap of 50 differentially expressed transcripts with lowest p values for a, BioClay vs. water, b, LDH vs. water, and c, naked dsRNA (sucrase) vs Water. BioClay (sucrase dsRNA-LDH) and LDH treatments do not co-cluster in each dataset. d, PCA analysis to differentially expressed transcripts does not demonstrate any clustering or co-clustering of samples from BioClay, LDH, naked dsRNA or water treatments, showing multitranscript treatment-specific impacts are not readily evident. e, Euler diagram of up-regulated transcript counts for BioClay, LDH and naked dsRNA vs. water. Most transcripts are upregulated in all three treatments or in individual treatments. Only 24 transcripts are up-regulated (p < 0.05 and log fold change > 1) in both BioClay and LDH but not naked dsRNA treatments relative to water, with none having identified abiotic stress-related functions (for example, HSps or WRKY, NAC, MYB and AP2/ERF TFs) in this subset. f. Euler diagram of down-regulated transcript counts for BioClay, LDH and naked dsRNA vs. water. Similarly, only 7 transcripts are down-regulated (p < 0.05 and log fold change < −1) in both BioClay and LDH but not naked dsRNA treatments relative to water. These transcripts also did not have identified abiotic stress functions. Total RNA was extracted from leaf tissue 10 days after foliar application (n = 3 for each treatment). Transcript expression analyses including generation of adjusted p-values were performed on generated Illumina paired-end read files using DESeq2 following adapter trimming and QC by Trim Galore and pseudoalignment using Kallisto v.0.46.1. Euler diagrams were plotted using the Eulerr R package v.6.1.1.

Extended Data Fig. 4 4 k-mer based selection of target transcript regions with reduced off-target homology.

By minimizing the size of the union of 14nt canonical k-mer sets derived from an incrementing transcript window of 400nt and the off-target transcriptomes of Homo sapiens (human), Apis mellifera (European honeybee), Apis florea (dwarf honeybee), Apis dorsata (giant honeybee), Apis cerana (eastern honeybee) and Danaus plexippus (monarch butterfly), regions of least homology were identified. Within these regions, primers with 5’ T7 promoter sequences were designed via Primer3 to generate amplicons of approximately 300 bp. This approach allowed for rapid dsRNA design on a complete whitefly transcriptome basis.

Extended Data Fig. 5 dsRNA loading on LDH to form dsRNA-LDH (BioClay) complex remains complete and consistent pre- and post-feeding.

dsRNAs in dsRNA-LDH complexes present in artificial diet remained completely loaded on LDH after 6 days of feeding, with whitefly mortality not linked to free dsRNAs in the diet. In vitro synthesized Ace1, AQP1, Vhaa and zfp dsRNAs were mixed with LDH at a dsRNA-LDH mass ratio of 1:4. For the post-feeding agarose gel image (right), three replicate samples of naked dsRNA and dsRNA-LDH are shown. For the pre-feeding gel image (left), one sample is shown. Loaded dsRNA does not migrate through the gel and is retained in the well (indicated by the black arrow). M = 1 kb+ ladder.

Source data

Extended Data Fig. 6 Addition of adjuvants (Banjo and Supercharge Elite) to dsRNA-Cy3 and dsRNA-Cy3-LDH does not change nomalized absorption and fluorescence spectra of Cy3.

a-g, Absorption spectra are shown for Cy3-CTP, CMV2b dsRNA-Cy3 and CMV2b dsRNA-Cy3-LDH with and without adjuvants. While a shoulder was evident in the absorption spectrum, Cy3 showed maxima at 550 nm and 580 nm for the absorption and fluorescence spectra, respectively. The excitation wavelength for the Cy3 was 520 nm.

Source data

Extended Data Fig. 7 Addition of adjuvant (Banjo) improves the uptake and internalization of naked and BioClay released dsRNA into cotton leaves.

Confocal images of transverse cross-sections of cotton leaves 72 h post-application with Cy3-labelled-CMV2b dsRNA-LDH. Images are shown for Cy3-CTP only; dsRNA-Cy3; dsRNA-Cy3-Banjo; dsRNA-Cy3-LDH; and dsRNA-Cy3-LDH-Banjo. Cy3-labelled dsRNA was detected within the spongy mesophyll and vascular bundle after dsRNA-Banjo and dsRNA-LDH with or without Banjo treatments, whereas the fluorescence signal remained visible on the surface of the leaf post dsRNA treatments. Bright-field (BF) images (column 1), Cy3 fluorescence images (column 2) and merged images (column 3) are shown. Scale bar = 100 μm.

Extended Data Fig. 8 Foliar applied naked and BioClay released dsRNA translocate from upper to lower leaves in cotton plants.

CMV2b dsRNA signal was detected in northern blot analysis in untreated lowermost cotton leaves 48 h post foliar application with naked CMV2b dsRNA and CMV2b dsRNA-LDH mixed with Banjo adjuvant on the uppermost leaves. For the northern image, three replicate samples of naked dsRNA and dsRNA-LDH are shown, and equal RNA loading is shown in the lower panel.

Source data

Extended Data Fig. 9 Whitefly nymphs take up dsRNA in detached cotton leaf dip assays.

Nymph infested cotton leaf petioles were dipped in water (control) or Cy3-labelled CMV2b dsRNA for 72 h at room temperature. Confocal microscopy of whole nymphs illustrates the localization of the Cy3 signal post 72 h feeding on Cy3-labelled CMV2b dsRNA solution. Nymphs fed on detached leaves dipped in water did not show a fluorescent signal. Bright-field (BF) image (column 1), Cy3 fluorescence image (column 2) and merged image of the two (column 3) are shown. Scale bar = 100 µm.

Extended Data Fig. 10 Uptake of abaxially-applied dsRNA by adult whiteflies on the abaxial surface of intact mature cotton leaves.

Cy3-labelled CMV2b dsRNA was applied with and without Banjo adjuvant on the abaxial (lower) surface of the cotton leaves and incubated at room temperature for 24 h. Adult whiteflies were released into the clip cage, also on the abaxial surface, and allowed to feed for a further 48 h. Confocal microscopy of the whole insect fed on dsRNA with or without adjuvant indicates localization of Cy3-labelled dsRNA in the whitefly gut, whereas control whiteflies fed on control (water) plants did not show a fluorescent signal. Bright-field (BF) image (column 1), Cy3 fluorescence image (column 2) and merged image of the two (column 3) are shown. Scale bar = 100 µm.

Supplementary information

Supplementary Information

Supplementary Figs. 1 and 2, Source data Supplementary Fig. 1.

Reporting Summary

Supplementary Table 1

Supplementary Method and Results Tables 1–5.

Source data

Source Data Fig. 1

Statistical source data and unprocessed gel.

Source Data Fig. 2

Statistical source data.

Source Data Fig. 3

Statistical source data.

Source Data Fig. 4

Statistical source data.

Source Data Fig. 6

Unprocessed gel and northern blots.

Source Data Fig. 7

Statistical source data.

Source Data Extended Data Fig. 1

Statistical source data.

Source Data Extended Data Fig. 5

Unprocessed gel.

Source Data Extended Data Fig. 6

Statistical source data.

Source Data Extended Data Fig. 8

Unprocessed northern blot.

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Jain, R.G., Fletcher, S.J., Manzie, N. et al. Foliar application of clay-delivered RNA interference for whitefly control. Nat. Plants 8, 535–548 (2022). https://doi.org/10.1038/s41477-022-01152-8

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