Abstract
Next-generation sequencing has opened up new avenues for the identification of microRNAs (miRNAs) and their corresponding roles in abiotic and biotic stress responses. Recently, a plethora of evidence suggests a canonical action of miRNA–mRNA interactions to regulate plant systems biology at the posttranscriptional level, thus leading to the gain or loss of genetic adaptation in plants. In this chapter, we present a detailed protocol for the identification of miRNA targets using six different prediction tools.
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References
Meyers BC, Axtell MJ, Bartel B, Bartel DP, Baulcombe D, Bowman JL, Cao X, Carrington JC, Chen X, Green PJ, Griffiths-Jones S, Jacobsen SE, Mallory AC, Martienssen RA, Poethig RS, Qi Y, Vaucheret H, Voinnet O, Watanabe Y, Weigel D, Zhu JK (2008) Criteria for annotation of plant MicroRNAs. Plant Cell 20:3186–3190
Rhoades MW, Reinhart BJ, Lim LP, Burge CB, Bartel B, Bartel DP (2002) Prediction of plant microRNA targets. Cell 110:513–520
Axtell MJ (2013) Classification and comparison of small RNAs from plants. Annu Rev Plant Biol 64:137–159
Dai X, Zhuang Z, Zhao PX (2011) Computational analysis of miRNA targets in plants: current status and challenges. Brief Bioinform 12:115–121
Bonnet E, He Y, Billiau K, Van de Peer Y (2010) TAPIR, a web server for the prediction of plant microRNA targets, including target mimics. Bioinformatics 26:1566–1568
Li F, Orban R, Baker B (2012) SoMART: a web server for plant miRNA, tasiRNA and target gene analysis. Plant J 70:891–901
Dai X, Zhuang Z, Zhao PX (2018) psRNATarget: a plant small RNA target analysis server (2017 release). Nucleic Acids Res 46(W1):W49–W54
Fahlgren N, Howell MD, Kasschau KD, Chapman EJ, Sullivan CM, Cumbie JS, Givan SA, Law TF, Grant SR, Dangl JL, Carrington JC (2007) High-throughput sequencing of Arabidopsis microRNAs: evidence for frequent birth and death of MIRNA genes. PLoS One 2:e219
Wu HJ, Ma YK, Chen T, Wang M, Wang XJ (2012) PsRobot: a web-based plant small RNA meta-analysis toolbox. Nucleic Acids Res 40:W22–W28
Ma X, Liu C, Gu L, Mo B, Cao X, Chen X (2018) TarHunter, a tool for predicting conserved microRNA targets and target mimics in plants. Bioinformatics 34:1574–1576
Addo-Quaye C, Miller W, Axtell MJ (2009) CleaveLand: a pipeline for using degradome data to find cleaved small RNA targets. Bioinformatics 25:130–131
Zhang L, Qin C, Mei J, Chen X, Wu Z, Luo X, Cheng J, Tang X, Hu K, Li SC (2017) Identification of microRNA targets of Capsicum spp. using MiRTrans—a trans-Omics approach. Front Plant Sci 8:495
Fahlgren N, Carrington JC (2010) miRNA target prediction in plants. In: Meyers B, Green P (eds) Plant MicroRNAs, Methods in molecular biology (methods and protocols), vol 592. Humana Press
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Sablok, G., Yang, K., Wen, X. (2019). Protocols for miRNA Target Prediction in Plants. In: Laganà, A. (eds) MicroRNA Target Identification. Methods in Molecular Biology, vol 1970. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-9207-2_5
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DOI: https://doi.org/10.1007/978-1-4939-9207-2_5
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