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Potent and specific genetic interference by double-stranded RNA in Caenorhabditis elegans

Author

Listed:
  • Andrew Fire

    (Carnegie Institution of Washington)

  • SiQun Xu

    (Carnegie Institution of Washington)

  • Mary K. Montgomery

    (Carnegie Institution of Washington)

  • Steven A. Kostas

    (Carnegie Institution of Washington
    Biology Graduate Program, Johns Hopkins University)

  • Samuel E. Driver

    (Program in Molecular Medicine, University of Massachusetts Cancer Center)

  • Craig C. Mello

    (Program in Molecular Medicine, University of Massachusetts Cancer Center)

Abstract

Experimental introduction of RNA into cells can be used in certain biological systems to interfere with the function of an endogenous gene1,2. Such effects have been proposed to result from a simple antisense mechanism that depends on hybridization between the injected RNA and endogenous messenger RNA transcripts. RNA interference has been used in the nematode Caenorhabditis elegans to manipulate gene expression3,4. Here we investigate the requirements for structure and delivery of the interfering RNA. To our surprise, we found that double-stranded RNA was substantially more effective at producing interference than was either strand individually. After injection into adult animals, purified single strands had at most a modest effect, whereas double-stranded mixtures caused potent and specific interference. The effects of this interference were evident in both the injected animals and their progeny. Only a few molecules of injected double-stranded RNA were required per affected cell, arguing against stochiometric interference with endogenous mRNA and suggesting that there could be a catalytic or amplification component in the interference process.

Suggested Citation

  • Andrew Fire & SiQun Xu & Mary K. Montgomery & Steven A. Kostas & Samuel E. Driver & Craig C. Mello, 1998. "Potent and specific genetic interference by double-stranded RNA in Caenorhabditis elegans," Nature, Nature, vol. 391(6669), pages 806-811, February.
    • Handle: RePEc:nat:nature:v:391:y:1998:i:6669:d:10.1038_35888
    DOI: 10.1038/35888
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    1. Ian F. Price & Jillian A. Wagner & Benjamin Pastore & Hannah L. Hertz & Wen Tang, 2023. "C. elegans germ granules sculpt both germline and somatic RNAome," Nature Communications, Nature, vol. 14(1), pages 1-17, December.
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    4. Kyle A McQuisten & Andrew S Peek, 2009. "Comparing Artificial Neural Networks, General Linear Models and Support Vector Machines in Building Predictive Models for Small Interfering RNAs," PLOS ONE, Public Library of Science, vol. 4(10), pages 1-14, October.
    5. Brian Hauge & Christopher Oggero & Nicole Nguyen & Changlin Fu & Fenggao Dong, 2009. "Single Tube, High Throughput Cloning of Inverted Repeat Constructs for Double-Stranded RNA Expression," PLOS ONE, Public Library of Science, vol. 4(9), pages 1-7, September.
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    10. Chai, Sen & Menon, Anoop, 2019. "Breakthrough recognition: Bias against novelty and competition for attention," Research Policy, Elsevier, vol. 48(3), pages 733-747.
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    12. Miaowei Mao & Yajie Qian & Wenyao Zhang & Siyu Zhou & Zefeng Wang & Xianjun Chen & Yi Yang, 2023. "Controlling protein stability with SULI, a highly sensitive tag for stabilization upon light induction," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    13. Gersbach, Hans & Sorger, Gerhard & Amon, Christian, 2018. "Hierarchical growth: Basic and applied research," Journal of Economic Dynamics and Control, Elsevier, vol. 90(C), pages 434-459.
    14. Li-Xin Ma & Rong-Tao He & Shu-Yan Yan & Wen-Jia Yang, 2022. "RNAi Suppression of Hormone Receptor HR3 Blocks Larval Molting and Metamorphosis in the Cigarette Beetle, Lasioderma serricorne," Agriculture, MDPI, vol. 12(8), pages 1-10, August.
    15. Sen Chai, 2017. "Near Misses in the Breakthrough Discovery Process," Organization Science, INFORMS, vol. 28(3), pages 411-428, June.
    16. Shew, Aaron M. & Danforth, Diana M. & Nalley, Lawton L. & Nayga, Rodolfo M. Jr. & Tsiboe, Francis & Dixon, Bruce L., 2016. "Consumers’ Willingness-To-Pay for RNAi versus Bt Rice: Are all biotechnologies the same?," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 235110, Agricultural and Applied Economics Association.
    17. Arnaud Segers & Joachim Carpentier & Frédéric Francis & Rudy Caparros Megido, 2023. "Gene Silencing of laccase 1 Induced by Double-Stranded RNA in Callosobruchus maculatus (Fabricius 1775) (Coleoptera: Chrysomelidae) Suggests RNAi as a Potential New Biotechnological Tool for Bruchid’s," Agriculture, MDPI, vol. 13(2), pages 1-19, February.
    18. Takasaki, Shigeru & Kawamura, Yoshihoro, 2007. "Using radial basis function networks and significance testing to select effective siRNA sequences," Computational Statistics & Data Analysis, Elsevier, vol. 51(12), pages 6476-6487, August.
    19. Ke, Qing, 2020. "The citation disadvantage of clinical research," Journal of Informetrics, Elsevier, vol. 14(1).
    20. Jiahui Zhang & Huiyuan Li & Xue Zhong & Jinfu Tian & Arnaud Segers & Lanqin Xia & Frédéric Francis, 2022. "RNA-Interference-Mediated Aphid Control in Crop Plants: A Review," Agriculture, MDPI, vol. 12(12), pages 1-20, December.
    21. Loet Leydesdorff & Floortje Alkemade & Gaston Heimeriks & Rinke Hoekstra, 2015. "Patents as instruments for exploring innovation dynamics: geographic and technological perspectives on “photovoltaic cells”," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(1), pages 629-651, January.
    22. Zahra Narimani & Hamid Beigy & Ashar Ahmad & Ali Masoudi-Nejad & Holger Fröhlich, 2017. "Expectation propagation for large scale Bayesian inference of non-linear molecular networks from perturbation data," PLOS ONE, Public Library of Science, vol. 12(2), pages 1-16, February.
    23. Daniele Rotolo & Ismael Rafols & Michael Hopkins & Loet Leydesdorff, 2014. "Scientometric Mapping as a Strategic Intelligence Tool for the Governance of Emerging Technologies," SPRU Working Paper Series 2014-10, SPRU - Science Policy Research Unit, University of Sussex Business School.
    24. Wei-Jie Pan & Chi-Wei Chen & Yen-Wei Chu, 2011. "siPRED: Predicting siRNA Efficacy Using Various Characteristic Methods," PLOS ONE, Public Library of Science, vol. 6(11), pages 1-7, November.

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