Abstract
MicroRNAs (miRNAs) are endogenous non-coding small RNAs, which regulate gene expression at the post-transcriptional level. A large number of studies have revealed that they play key roles in diverse life activities, such as growth and development. In the last decade, deep sequencing technology has generated substantial small RNA sequencing (sRNA-Seq) data. Meanwhile, numerous tools have been developed to identify miRNAs from these sRNA-Seq data, resulting in a surge of miRNA annotations. Among these tools, the series of miRDeep-P and miRDeep-P2 have been widely used in plant miRNA annotation. Here, we employed miRDeep-P2 to demonstrate the plant miRNA annotation processes step by step using the deep sequencing data.
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References
Bartel DP (2009) MicroRNAs: target recognition and regulatory functions. Cell 136(2):215–233
Voinnet O (2009) Origin, biogenesis, and activity of plant microRNAs. Cell 136(4):669–687
Yang XZ, Fishilevich E, German MA et al (2021) Elucidation of the microRNA transcriptome in Western corn rootworm reveals its dynamic and evolutionary complexity. Genom Proteom Bioinf. https://doi.org/10.1016/j.gpb.2019.03.008
Shi Y, Xia H, Cheng X et al (2021) Genome-wide miRNA analysis and integrated network for flavonoid biosynthesis in Osmanthus fragrans. BMC Genomics 22(1):141
Zhao YX, Kuang Z, Wang Y et al (2021) MicroRNA annotation in plants: current status and challenges. Brief Bioinform. https://doi.org/10.1093/bib/bbab075
Kuang Z, Wang Y, Li L et al (2019) miRDeep-P2: accurate and fast analysis of the microRNA transcriptome in plants. Bioinformatics 35(14):2521–2522
Yang XZ, Li L (2011) miRDeep-P: a computational tool for analyzing the microRNA transcriptome in plants. Bioinformatics 27(18):2614–2615
Taylor RS, Tarver JE, Hiscock SJ et al (2014) Evolutionary history of plant microRNAs. Trends Plant Sci 19(3):175–182
Langmead B, Trapnell C, Pop M et al (2009) Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol 10(3):R25
Langmead B, Salzberg SL (2012) Fast gapped-read alignment with bowtie 2. Nat Methods 9(4):357–359
Hofacker IL (2003) Vienna RNA secondary structure server. Nucleic Acids Res 31(13):3429–3431
Brown J, Pirrung M, McCue LA (2017) FQC dashboard: integrates FastQC results into a web-based, interactive, and extensible FASTQ quality control tool. Bioinformatics 33(19):3137–3139
Kechin A, Boyarskikh U, Kel A et al (2017) cutPrimers: a new tool for accurate cutting of primers from reads of targeted next generation sequencing. J Comput Biol 24(11):1138–1143
Axtell MJ, Meyers BC (2018) Revisiting criteria for plant MicroRNA annotation in the era of big data. Plant Cell 30(2):272–284
Guo ZL, Kuang Z, Wang Y et al (2020) PmiREN: a comprehensive encyclopedia of plant miRNAs. Nucleic Acids Res 48(D1):D1114–D1121
Kim VN (2005) MicroRNA biogenesis: coordinated cropping and dicing. Nat Rev Mol Cell Biol 6(5):376–385
Neilsen CT, Goodall GJ, Bracken CP (2012) IsomiRs–the overlooked repertoire in the dynamic microRNAome. Trends Genet 28(11):544–549
Zhang XM, Zhao HW, Gao S et al (2011) Arabidopsis Argonaute 2 regulates innate immunity via miRNA393*-mediated silencing of a Golgi-localized SNARE gene, MEMB12. Mol Cell 42(3):356–366
Liu WW, Meng J, Cui J et al (2017) Characterization and function of MicroRNA*s in plants. Front Plant Sci 8:2200
Palatnik JF, Allen E, Wu XL et al (2003) Control of leaf morphogenesis by microRNAs. Nature 425(6955):257–263
Wang Y, Kuang Z, Li L et al (2020) A bioinformatics pipeline to accurately and efficiently analyze the MicroRNA transcriptomes in plants. J Vis Exp. https://doi.org/10.3791/59864
Acknowledgement
This work was supported by the Beijing Academy of Agriculture and Forestry Sciences (BAAFS) (KJCX201907-2 and KJCX20200204 to X.Y, and QNJJ202019 to Y.Z.) and the National Natural Science Foundation of China (NSFC) (32070248 to X.Y.).
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Kuang, Z., Zhao, Y., Yang, X. (2023). Plant MicroRNA Identification and Annotation Using Deep Sequencing Data. In: Rani, S. (eds) MicroRNA Profiling. Methods in Molecular Biology, vol 2595. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-2823-2_17
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DOI: https://doi.org/10.1007/978-1-0716-2823-2_17
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