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.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Didion JP, Martin M, Collins FS (2017) Atropos: specific, sensitive, and speedy trimming of sequencing reads. PeerJ 5:e3720
Martin M (2011) Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnetjournal 17:10–12
Bolger AM, Lohse M, Usadel B (2014) Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30:2114–2120
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
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
Tsuji J, Weng Z (2016) DNApi: a De Novo Adapter prediction algorithm for small RNA sequencing data. PLoS One 11:e0164228
Jiang H, Wong WH (2008) SeqMap: mapping massive amount of oligonucleotides to the genome. Bioinformatics 24:2395–2396
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
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
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
Johnson NR, Yeoh JM, Coruh C, Axtell MJ (2016) Improved placement of multi-mapping Small RNAs. G3 (Bethesda) 6:2103–2111
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
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
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
Floyd SK, Bowman JL (2004) Ancient microRNA target sequences in plants. Nature 428:485–486
Zhang B, Pan X, Cannon CH, Cobb GP, Anderson TA (2006) Conservation and divergence of plant microRNA genes. Plant J 46:243–259
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
Kozomara A, Griffiths-Jones S (2014) miRBase: annotating high confidence microRNAs using deep sequencing data. Nucleic Acids Res 42:D68–D73
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
Taylor RS, Tarver JE, Hiscock SJ, Donoghue PCJ (2014) Evolutionary history of plant microRNAs. Trends Plant Sci 19:175–182
Taylor RS, Tarver JE, Foroozani A, Donoghue PCJ (2017) MicroRNA annotation of plant genomes − do it right or not at all. BioEssays 39:1600113
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
Robinson MD, McCarthy DJ, Smyth GK (2010) edgeR: a bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 26:139–140
Love MI, Huber W, Anders S (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15:550
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
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
Robinson JT, Thorvaldsdóttir H, Winckler W, Guttman M, Lander ES, Getz G, Mesirov JP (2011) Integrative genomics viewer. Nat Biotechnol 29:24–26
Thorvaldsdottir H, Robinson JT, Mesirov JP (2013) Integrative Genomics Viewer (IGV): high-performance genomics data visualization and exploration. Brief Bioinform 14:178–192
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
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.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Science+Business Media, LLC, part of Springer Nature
About this protocol
Cite this protocol
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
Download citation
DOI: https://doi.org/10.1007/978-1-4939-9042-9_4
Published:
Publisher Name: Humana Press, New York, NY
Print ISBN: 978-1-4939-9041-2
Online ISBN: 978-1-4939-9042-9
eBook Packages: Springer Protocols