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Efficient search algorithms for RNAi target detection

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Abstract

RNA interference (RNAi) is a posttranscriptional gene silencing mechanism used to study gene functions, inhibit viral activities, and treat diseases therapeutically. However, RNAi has off-target effects—non-target genes can be unintentionally silenced. Therefore, target validation through target detection is crucial for the success of RNAi experiments. Effective target detection must examine each gene expressed by an organism, making computational efficiency a critical issue. We develop efficient sequential and parallel search algorithms using RNA string kernels, which model mismatches, G-U wobbles, bulges, and the seed region in the hybridization between an siRNA and its target mRNA. Empirical results demonstrate that our algorithms achieved speedups of six orders of magnitude over the alignment algorithm based on tests in the organisms of S. pombe, C. elegans, D. melanogaster, and human. Our design strategy also leads to a framework for efficient, flexible, and portable string search algorithms allowing for inexact matches.

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References

  1. Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ (1990) Basic local alignment search tool. J Mol Biol 215:403–410

    Google Scholar 

  2. Check E (2004) Hopes rise for RNA therapy as mouse study hits target. Nature 432:136

    Article  Google Scholar 

  3. Dillin A (2003) The specifics of small interfering RNA specificity. Proc Nat Acad Sci USA 100:6289–6291

    Article  Google Scholar 

  4. Elbashir SM, Harborth J, Weber K, Tuschl T (2002) Analysis of gene function in somatic mammalian cells using small interfering RNAs. Method 26:199–213

    Article  Google Scholar 

  5. Elbashir SM, Martinez J, Patkaniowska A, Lendeckel W, Tuschl T (2001) Functional anatomy of siRNA for mediating efficient RNAi in Drosophila melanogaster embryo lysate. EMBO J 20(23):6877–6888

    Article  Google Scholar 

  6. Fire A, Xu SQ, Montgomery MK, Kostas SA, Driver SE, Mello CC (1998) Potent and specific genetic interference by double-stranded RNA in Caenorhabditis elegans. Nature 391(6669):806–811

    Article  Google Scholar 

  7. Halaas A, Svingen B, Nedland M, Sætrom P, Snøve O Jr, Birkeland OR (2004) A recursive MISD architecture for pattern matching. IEEE Trans Very Larg Scale Integr Syst 12(7):727–734

    Article  Google Scholar 

  8. Horesh Y, Amir A, Michaeli S, Unger R (2003) A rapid method for detection of putative RNAi target genes in genomic data. Bioinf 19(Suppl 2):ii73–ii80

    Google Scholar 

  9. Jackson AL, Bartz SR, Schelter J, Kobayashi SV, Burchard J, Mao M, Li B, Cavet G, Linsley PS (2003) Expression profiling reveals off-target gene regulation by RNAi. Nature Biotechnol 21(6):635–637

    Article  Google Scholar 

  10. Khvorova A, Reynolds A, Jayasena SD (2003) Functional siRNAs and miRNAs exhibit strand bias. Cell 115:209–216

    Article  Google Scholar 

  11. Knuth DE, Morris JH, Pratt VR (1977) Fast pattern matching in strings. SIAM J Comput 6(1):323–350

    Article  MATH  MathSciNet  Google Scholar 

  12. Leslie C, Eskin E, Noble WS (2002) The spectrum kernel: a string kernel for SVM protein classification. In: Proceedings of the pacific symposium on bioinformatics, 2002, pp 564–575

  13. Lewis BP, Shih I-H, Jones-Rhoades MWW, Bartel DP, Burge CB (2003) Prediction of mammalian microRNA targets. Cell 115:787–798

    Article  Google Scholar 

  14. Lim LP, Glasner ME, Yekta S, Burge CB, Bartel DP (2003) Vertebrate microRNA genes. Sci 299:1540

    Article  Google Scholar 

  15. Lodhi H, Saunders C, Shawe-Taylor J, Cristianini N, Watkins C (2002) Text classification using string kernels. J Mach Learn Res 2:419–444

    Article  MATH  Google Scholar 

  16. Needleman SB, Wunsch CD (1970) J Mol Biol 48:443–453

    Article  Google Scholar 

  17. Qiu S, Adema CM, Lane T (2005) A computational study of off-target effects of RNA interference. Nucl Acid Res 33:1834–1847

    Article  Google Scholar 

  18. Qiu S, Lane T (2006) RNA string kernels for RNAi off-target evaluation. Int J Bioinf Res Appl (IJBRA) 2(2):132–146

    Google Scholar 

  19. Saxena S, Jonsson ZO, Dutta A (2003) Small RNAs with imperfect match to endogenous mRNA repress translation. J Biol Chem 278(45):44312–44319

    Article  Google Scholar 

  20. Smith TF, Waterman MS (1981) J Mol Biol 147(1):195–197

    Google Scholar 

  21. Snøve O Jr, Holen T (2004) Many commonly used siRNAs risk off-target activity. Biochem Biophys Res Commun 319:256–263

    Article  Google Scholar 

  22. Tuschl T, Zamore PD, Lehmann R, Bartel DP, Sharp PA (1999) Targeted mRNA degradation by double-stranded RNA in vitro. Genes Dev 13:3191–3197

    Article  Google Scholar 

  23. Vapnik VN (1998) Statistical learning theory. Wiley

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Authors and Affiliations

  1. Department of Computer Science, University of New Mexico, Albuquerque, NM, 87131, USA

    Shibin Qiu & Terran Lane

  2. Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, USA

    Cundong Yang

Authors
  1. Shibin Qiu
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  2. Terran Lane
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  3. Cundong Yang
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Correspondence to Terran Lane.

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Qiu, S., Lane, T. & Yang, C. Efficient search algorithms for RNAi target detection. J Supercomput 42, 303–319 (2007). https://doi.org/10.1007/s11227-007-0121-9

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  • DOI: https://doi.org/10.1007/s11227-007-0121-9

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