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Bioinformatic Analysis of Small RNA Sequencing Libraries

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Plant MicroRNAs

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1932))

Abstract

Bioinformatic analysis of small RNA sequencing libraries consists of transforming a series of small RNA sequencing experiment fastq files into a table containing small RNA sequences and their abundance. This is achieved by cleaning the reads, aligning the cleaned reads to a reference, and parsing the alignment results. In this protocol we present the most common option, and the rationale, for each of these steps.

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References

  1. Didion JP, Martin M, Collins FS (2017) Atropos: specific, sensitive, and speedy trimming of sequencing reads. PeerJ 5:e3720

    Article  Google Scholar 

  2. Martin M (2011) Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnetjournal 17:10–12

    Google Scholar 

  3. Bolger AM, Lohse M, Usadel B (2014) Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30:2114–2120

    Article  CAS  Google Scholar 

  4. Chávez-Montes RA, Rosas-Cárdenas FF, De Paoli E, Accerbi M, Rymarquis LA, Mahalingam G, Marsch-Martínez N, Meyers BC, Green PJ, de Folter S (2014) Sample sequencing of vascular plants demonstrates widespread conservation and divergence of microRNAs. Nat Commun 5:3722

    Article  Google Scholar 

  5. You C, Cui J, Wang H, Qi X, Kuo L-Y, Ma H, Gao L, Mo B, Chen X (2017) Conservation and divergence of small RNA pathways and microRNAs in land plants. Genome Biol 18:158

    Article  Google Scholar 

  6. Tsuji J, Weng Z (2016) DNApi: a De Novo Adapter prediction algorithm for small RNA sequencing data. PLoS One 11:e0164228

    Article  Google Scholar 

  7. Jiang H, Wong WH (2008) SeqMap: mapping massive amount of oligonucleotides to the genome. Bioinformatics 24:2395–2396

    Article  CAS  Google Scholar 

  8. Nawrocki EP, Burge SW, Bateman A, Daub J, Eberhardt RY, Eddy SR, Floden EW, Gardner PP, Jones TA, Tate J, Finn RD (2015) Rfam 12.0: updates to the RNA families database. Nucleic Acids Res 43:D130–D137

    Article  CAS  Google Scholar 

  9. Kalvari I, Argasinska J, Quinones-Olvera N, Nawrocki EP, Rivas E, Eddy SR, Bateman A, Finn RD, Petrov AI (2018) Rfam 13.0: shifting to a genome-centric resource for non-coding RNA families. Nucleic Acids Res 46:D335–D342

    Article  CAS  Google Scholar 

  10. Langmead B, Trapnell C, Pop M, Salzberg SL (2009) Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol 10:R25

    Article  Google Scholar 

  11. Johnson NR, Yeoh JM, Coruh C, Axtell MJ (2016) Improved placement of multi-mapping Small RNAs. G3 (Bethesda) 6:2103–2111

    Article  CAS  Google Scholar 

  12. Axtell MJ, Meyers BC (2018) Revisiting criteria for plant miRNA annotation in the era of big data. Plant Cell 30(2):272–284. https://doi.org/10.1105/tpc.17.00851

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, Marth G, Abecasis G, Durbin R (2009) The sequence alignment/map format and SAMtools. Bioinformatics 25:2078–2079

    Article  Google Scholar 

  14. Lorenz R, Bernhart SH, Höner zu Siederdissen C, Tafer H, Flamm C, Stadler PF, Hofacker IL (2011) ViennaRNA Package 2.0. Alg Mol Biol 6:26

    Article  Google Scholar 

  15. Floyd SK, Bowman JL (2004) Ancient microRNA target sequences in plants. Nature 428:485–486

    Article  CAS  Google Scholar 

  16. Zhang B, Pan X, Cannon CH, Cobb GP, Anderson TA (2006) Conservation and divergence of plant microRNA genes. Plant J 46:243–259

    Article  CAS  Google Scholar 

  17. Jasinski S, Vialette-Guiraud ACM, Scutt CP (2010) The evolutionary-developmental analysis of plant microRNAs. Philos Trans R Soc Lond Ser B Biol Sci 365:469–476

    Article  CAS  Google Scholar 

  18. Kozomara A, Griffiths-Jones S (2014) miRBase: annotating high confidence microRNAs using deep sequencing data. Nucleic Acids Res 42:D68–D73

    Article  CAS  Google Scholar 

  19. Lei J, Sun Y (2014) miR-PREFeR: an accurate, fast and easy-to-use plant miRNA prediction tool using small RNA-Seq data. Bioinformatics 30:2837–2839

    Article  CAS  Google Scholar 

  20. Taylor RS, Tarver JE, Hiscock SJ, Donoghue PCJ (2014) Evolutionary history of plant microRNAs. Trends Plant Sci 19:175–182

    Article  CAS  Google Scholar 

  21. Taylor RS, Tarver JE, Foroozani A, Donoghue PCJ (2017) MicroRNA annotation of plant genomes − do it right or not at all. BioEssays 39:1600113

    Article  Google Scholar 

  22. Lawrence M, Huber W, Pagès H, Aboyoun P, Carlson M, Gentleman R, Morgan MT, Carey VJ (2013) Software for Computing and Annotating Genomic Ranges. PLoS Comput Biol 9:e1003118

    Article  CAS  Google Scholar 

  23. Robinson MD, McCarthy DJ, Smyth GK (2010) edgeR: a bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 26:139–140

    Article  CAS  Google Scholar 

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

    Article  Google Scholar 

  25. Tarazona S, García-Alcalde F, Dopazo J, Ferrer A, Conesa A (2011) Differential expression in RNA-seq: a matter of depth. Genome Res 21:2213–2223

    Article  CAS  Google Scholar 

  26. Wang F, Johnson NR, Coruh C, Axtell MJ (2016) Genome-wide analysis of single non-templated nucleotides in plant endogenous siRNAs and miRNAs. Nucleic Acids Res 44:7395–7405

    Article  CAS  Google Scholar 

  27. Robinson JT, Thorvaldsdóttir H, Winckler W, Guttman M, Lander ES, Getz G, Mesirov JP (2011) Integrative genomics viewer. Nat Biotechnol 29:24–26

    Article  CAS  Google Scholar 

  28. Thorvaldsdottir H, Robinson JT, Mesirov JP (2013) Integrative Genomics Viewer (IGV): high-performance genomics data visualization and exploration. Brief Bioinform 14:178–192

    Article  CAS  Google Scholar 

  29. Cheng C-Y, Krishnakumar V, Chan AP, Thibaud-Nissen F, Schobel S, Town CD (2017) Araport11: a complete reannotation of the Arabidopsis thaliana reference genome. Plant J 89:789–804

    Article  CAS  Google Scholar 

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Acknowledgments

Work in the SDF laboratory was financed by the Mexican National Council of Science and Technology (CONACyT) grants CB-2012-177739 and FC-2015-2/1061.

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Correspondence to Ricardo A. Chávez Montes .

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Chávez Montes, R.A., Jaimes-Miranda, F., de Folter, S. (2019). Bioinformatic Analysis of Small RNA Sequencing Libraries. In: de Folter, S. (eds) Plant MicroRNAs. Methods in Molecular Biology, vol 1932. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-9042-9_4

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  • DOI: https://doi.org/10.1007/978-1-4939-9042-9_4

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  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-9041-2

  • Online ISBN: 978-1-4939-9042-9

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