{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,8]],"date-time":"2026-04-08T03:24:37Z","timestamp":1775618677562,"version":"3.50.1"},"reference-count":114,"publisher":"Oxford University Press (OUP)","issue":"4","license":[{"start":{"date-parts":[[2017,10,20]],"date-time":"2017-10-20T00:00:00Z","timestamp":1508457600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001721","name":"Rijksuniversiteit Groningen","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001721","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019,7,19]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Small RNAs (sRNAs) are important short-length molecules with regulatory functions essential for plant development and plasticity. High-throughput sequencing of total sRNA populations has revealed that the largest share of sRNA remains uncategorized. To better understand the role of sRNA-mediated cellular regulation, it is necessary to create accurate and comprehensive catalogues of sRNA and their sequence features, a task that currently relies on nontrivial bioinformatic approaches. Although a large number of computational tools have been developed to predict features of sRNA sequences, these tools are mostly dedicated to microRNAs and none integrates the functionalities necessary to describe units from all sRNA pathways thus far discovered in plants. Here, we review the different classes of sRNA found in plants and describe available bioinformatics tools that can help in their detection and categorization.<\/jats:p>","DOI":"10.1093\/bib\/bbx136","type":"journal-article","created":{"date-parts":[[2017,10,1]],"date-time":"2017-10-01T07:06:40Z","timestamp":1506841600000},"page":"1181-1192","source":"Crossref","is-referenced-by-count":29,"title":["Computational tools for plant small RNA detection and categorization"],"prefix":"10.1093","volume":"20","author":[{"given":"Lionel","family":"Morgado","sequence":"first","affiliation":[]},{"given":"Frank","family":"Johannes","sequence":"additional","affiliation":[]}],"member":"286","published-online":{"date-parts":[[2017,10,20]]},"reference":[{"key":"2019100807483906600_bbx136-B1","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1038\/nature11247","article-title":"An integrated encyclopedia of DNA elements in the human genome","volume":"489","author":"Bernstein","year":"2012","journal-title":"Nature"},{"key":"2019100807483906600_bbx136-B2","doi-asserted-by":"crossref","first-page":"1650","DOI":"10.1089\/dna.2012.1681","article-title":"The small RNA-based odyssey of epigenetic information in plants: from cells to species","volume":"12","author":"Mirouze","year":"2012","journal-title":"DNA Cell Biol"},{"key":"2019100807483906600_bbx136-B3","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1146\/annurev-arplant-050312-120043","article-title":"Classification and comparison of small RNAs from plants","volume":"64","author":"Axtell","year":"2013","journal-title":"Annu Rev Plant Biol"},{"key":"2019100807483906600_bbx136-B4","doi-asserted-by":"crossref","first-page":"727","DOI":"10.1038\/nrm4085","article-title":"The expanding world of small RNAs in plants","volume":"16","author":"Borges","year":"2015","journal-title":"Nat Rev Mol Cell Biol"},{"issue":"2","key":"2019100807483906600_bbx136-B5","doi-asserted-by":"crossref","first-page":"1299","DOI":"10.1534\/genetics.106.069484","article-title":"Transcriptional interferences in cis natural antisense transcripts of humans and mice","volume":"176","author":"Osato","year":"2007","journal-title":"Genetics"},{"key":"2019100807483906600_bbx136-B6","doi-asserted-by":"crossref","first-page":"W467","DOI":"10.1093\/nar\/gkv555","article-title":"sRNAtoolbox: an integrated collection of small RNA research tools","volume":"43","author":"Rueda","year":"2015","journal-title":"Nucl Acids Res"},{"key":"2019100807483906600_bbx136-B7","doi-asserted-by":"crossref","first-page":"2059","DOI":"10.1093\/bioinformatics\/bts311","article-title":"The UEA sRNA workbench: a suite of tools for analysing and visualizing next generation sequencing microRNA and small RNA datasets","volume":"28","author":"Stocks","year":"2012","journal-title":"Bioinformatics"},{"issue":"20","key":"2019100807483906600_bbx136-B8","doi-asserted-by":"crossref","first-page":"2651","DOI":"10.1093\/bioinformatics\/btt457","article-title":"omiRas: a Web server for differential expression analysis of miRNAs derived from small RNA-Seq data","volume":"29","author":"M\u00fcller","year":"2013","journal-title":"Bioinformatics"},{"key":"2019100807483906600_bbx136-B9","doi-asserted-by":"crossref","first-page":"708.","DOI":"10.3389\/fpls.2014.00708","article-title":"plantDARIO: web based quantitative and qualitative analysis of small RNA-seq data in plants","volume":"5","author":"Patra","year":"2014","journal-title":"Front Plant Sci"},{"key":"2019100807483906600_bbx136-B10","doi-asserted-by":"crossref","first-page":"3147","DOI":"10.1093\/bioinformatics\/bts587","article-title":"ncPRO-seq: a tool for annotation and profiling of ncRNAs in sRNA-seq data","volume":"28","author":"Chen","year":"2012","journal-title":"Bioinformatics"},{"issue":"1","key":"2019100807483906600_bbx136-B11","doi-asserted-by":"crossref","first-page":"20","DOI":"10.1186\/s13040-016-0099-z","article-title":"SePIA: RNA and small RNA sequence processing, integration, and analysis","volume":"9","author":"Icay","year":"2016","journal-title":"BioData Min"},{"key":"2019100807483906600_bbx136-B12","doi-asserted-by":"crossref","DOI":"10.1093\/bioinformatics\/btx066","article-title":"CPSS 2.0: a computational platform update for the analysis of small RNA sequencing data","author":"Wan","year":"2017","journal-title":"Bioinformatics"},{"key":"2019100807483906600_bbx136-B13","doi-asserted-by":"crossref","first-page":"e34","DOI":"10.1093\/nar\/gkp1127","article-title":"SeqBuster, a bioinformatic tool for the processing and analysis of small RNAs datasets, reveals ubiquitous miRNA modifications in human embryonic cells","volume":"38","author":"Pantano","year":"2010","journal-title":"Nucl Acids Res"},{"key":"2019100807483906600_bbx136-B14","doi-asserted-by":"crossref","first-page":"180.","DOI":"10.1186\/s12859-017-1601-4","article-title":"QuickMIRSeq: a pipeline for quick and accurate quantification of both known miRNAs and isomiRs by jointly processing multiple samples from microRNA sequencing","volume":"18","author":"Zhao","year":"2017","journal-title":"BMC Bioinformatics"},{"key":"2019100807483906600_bbx136-B15","doi-asserted-by":"crossref","first-page":"38","DOI":"10.3389\/fbioe.2014.00038","article-title":"IsomiRage: from functional classification to differential expression of miRNA isoforms","volume":"2","author":"Muller","year":"2014","journal-title":"Front Bioeng Biotechnol"},{"key":"2019100807483906600_bbx136-B16","first-page":"W467","article-title":"sRNAbench: profiling of small RNAs and its sequence variants in single or multi-species high-throughput experiments","volume":"43","author":"Barturen","year":"2014","journal-title":"Methods Next Gen Seq"},{"key":"2019100807483906600_bbx136-B17","doi-asserted-by":"crossref","first-page":"2629","DOI":"10.1016\/j.febslet.2013.06.047","article-title":"isomiRex: web-based identification of microRNAs, isomiR variations and differential expression using next-generation sequencing datasets","volume":"587","author":"Sablok","year":"2013","journal-title":"FEBS Lett"},{"key":"2019100807483906600_bbx136-B18","doi-asserted-by":"crossref","first-page":"2521","DOI":"10.1093\/bioinformatics\/btt424","article-title":"isomiRID: a framework to identify microRNA isoforms","volume":"29","author":"De Oliveira","year":"2013","journal-title":"Bioinformatics"},{"key":"2019100807483906600_bbx136-B19","doi-asserted-by":"crossref","first-page":"3429","DOI":"10.1093\/nar\/gkg599","article-title":"Vienna RNA secondary structure server","volume":"31","author":"Hofacker","year":"2003","journal-title":"Nucl Acids Res"},{"key":"2019100807483906600_bbx136-B20","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1007\/978-1-60327-429-6_1","article-title":"UNAFold: software for nucleic acid folding and hybridization","volume":"453","author":"Markham","year":"2008","journal-title":"Methods Mol Biol"},{"key":"2019100807483906600_bbx136-B21","doi-asserted-by":"crossref","first-page":"179","DOI":"10.1186\/s12859-015-0594-0","article-title":"Mirinho: an efficient and general plant and animal pre-miRNA predictor for genomic and deep sequencing data","volume":"16","author":"Higashi","year":"2015","journal-title":"BMC Bioinformatics"},{"issue":"W1","key":"2019100807483906600_bbx136-B22","doi-asserted-by":"crossref","first-page":"W181","DOI":"10.1093\/nar\/gkw459","article-title":"miRNAFold: a Web server for fast miRNA precursor prediction in genomes","volume":"44","author":"Tav","year":"2016","journal-title":"Nucleic Acids Res"},{"key":"2019100807483906600_bbx136-B23","doi-asserted-by":"crossref","first-page":"11511","DOI":"10.1073\/pnas.0404025101","article-title":"Detection of 91 potential conserved plant microRNAs in Arabidopsis thaliana and Oryza sativa identifies important target genes","volume":"101","author":"Bonnet","year":"2004","journal-title":"Proc Natl Acad Sci USA"},{"issue":"6","key":"2019100807483906600_bbx136-B24","doi-asserted-by":"crossref","first-page":"787","DOI":"10.1016\/j.molcel.2004.05.027","article-title":"Computational identification of plant microRNAs and their targets, including a stress-induced miRNA","volume":"14","author":"Jones-Rhoades","year":"2004","journal-title":"Mol Cell"},{"key":"2019100807483906600_bbx136-B25","doi-asserted-by":"crossref","first-page":"359","DOI":"10.1093\/bioinformatics\/bti802","article-title":"Identification of plant microRNA homologs","volume":"22","author":"Dezulian","year":"2006","journal-title":"Bioinformatics"},{"key":"2019100807483906600_bbx136-B26","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1186\/1471-2164-6-119","article-title":"Computational evidence for hundreds of non-conserved plant microRNAs","volume":"6","author":"Lindow","year":"2005","journal-title":"BMC Genomics"},{"key":"2019100807483906600_bbx136-B27","doi-asserted-by":"crossref","first-page":"248","DOI":"10.6026\/97320630006248","article-title":"miRTour: plant miRNA and target prediction tool","volume":"6","author":"Milev","year":"2011","journal-title":"Bioinformation"},{"key":"2019100807483906600_bbx136-B28","doi-asserted-by":"crossref","first-page":"S16","DOI":"10.1186\/1471-2164-13-S7-S16","article-title":"C-mii: a tool for plant miRNA and target identification","volume":"13","author":"Numnark","year":"2012","journal-title":"BMC Genomics"},{"key":"2019100807483906600_bbx136-B29","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1007\/s11103-012-9885-2","article-title":"miRDeepFinder: a miRNA analysis tool for deep sequencing of plant small RNAs","volume":"80","author":"Xie","year":"2012","journal-title":"Plant Mol Biol"},{"key":"2019100807483906600_bbx136-B30","doi-asserted-by":"crossref","first-page":"1368","DOI":"10.1093\/bioinformatics\/btr153","article-title":"PlantMiRNAPred: efficient classification of real and pseudo plant pre-miRNAs","volume":"27","author":"Xuan","year":"2011","journal-title":"Bioinformatics"},{"key":"2019100807483906600_bbx136-B31","doi-asserted-by":"crossref","first-page":"3124","DOI":"10.1039\/C6MB00295A","article-title":"plantMirP: an efficient computational program for the prediction of plant pre-miRNA by incorporating knowledge-based energy features","volume":"12","author":"Yao","year":"2016","journal-title":"Mol Biosyst"},{"key":"2019100807483906600_bbx136-B32","doi-asserted-by":"crossref","first-page":"1","DOI":"10.4061\/2010\/495904","article-title":"NOVOMIR: de novo prediction of MicroRNA-coding regions in a single plant-genome","volume":"2010","author":"Teune","year":"2010","journal-title":"J Nucleic Acids"},{"key":"2019100807483906600_bbx136-B33","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1186\/1471-2105-14-83","article-title":"HuntMi: an efficient and taxon-specific approach in pre-miRNA identification","volume":"14","author":"Gudys","year":"2013","journal-title":"BMC Bioinformatics"},{"key":"2019100807483906600_bbx136-B34","doi-asserted-by":"crossref","first-page":"652979","DOI":"10.1155\/2012\/652979","article-title":"Plant microRNA prediction by supervised machine learning using C5.0 decision trees","volume":"2012","author":"Williams","year":"2012","journal-title":"J Nucleic Acids"},{"key":"2019100807483906600_bbx136-B35","doi-asserted-by":"crossref","first-page":"1215","DOI":"10.1093\/bioinformatics\/btr132","article-title":"SplamiR\u2013prediction of spliced miRNAs in plants","volume":"27","author":"Thieme","year":"2011","journal-title":"Bioinformatics"},{"key":"2019100807483906600_bbx136-B36","doi-asserted-by":"crossref","first-page":"6595","DOI":"10.1186\/s12859-014-0423-x","article-title":"Prediction of plant pre-microRNAs and their microRNAs in genome-scale sequences using structure-sequence features and support vector machine","volume":"15","author":"Meng","year":"2014","journal-title":"BMC Bioinformatics"},{"key":"2019100807483906600_bbx136-B37","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1186\/1471-2105-12-107","article-title":"MiRPara: a SVM-based software tool for prediction of most probable microRNA coding regions in genome scale sequences","volume":"12","author":"Wu","year":"2011","journal-title":"BMC Bioinformatics"},{"key":"2019100807483906600_bbx136-B38","doi-asserted-by":"crossref","first-page":"7200","DOI":"10.1093\/nar\/gkt466","article-title":"Computational prediction of the localization of microRNAs within their pre-miRNA","volume":"41","author":"Leclercq","year":"2013","journal-title":"Nucleic Acids Res"},{"key":"2019100807483906600_bbx136-B39","doi-asserted-by":"crossref","first-page":"e0126151","DOI":"10.1371\/journal.pone.0126151","article-title":"MiRduplexSVM: a high-performing miRNA-duplex prediction and evaluation methodology","volume":"10","author":"Karathanasis","year":"2015","journal-title":"PLoS One"},{"key":"2019100807483906600_bbx136-B40","doi-asserted-by":"crossref","first-page":"e27422","DOI":"10.1371\/journal.pone.0027422","article-title":"MaturePred: efficient identification of MicroRNAs within novel plant pre-miRNAs","volume":"6","author":"Xuan","year":"2011","journal-title":"PLoS One"},{"key":"2019100807483906600_bbx136-B41","doi-asserted-by":"crossref","first-page":"e0142753","DOI":"10.1371\/journal.pone.0142753","article-title":"MiRLocator: machine learning-based prediction of mature MicroRNAs within plant pre-miRNA sequences","volume":"10","author":"Cui","year":"2015","journal-title":"PLoS One"},{"key":"2019100807483906600_bbx136-B42","doi-asserted-by":"crossref","first-page":"740","DOI":"10.1261\/rna.035279.112","article-title":"ShortStack: comprehensive annotation and quantification of small RNA genes","volume":"19","author":"Axtell","year":"2013","journal-title":"RNA"},{"issue":"18","key":"2019100807483906600_bbx136-B43","doi-asserted-by":"crossref","first-page":"2614","DOI":"10.1093\/bioinformatics\/btr430","article-title":"miRDeep-P: a computational tool for analyzing the microRNA transcriptome in plants","volume":"27","author":"Yang","year":"2011","journal-title":"Bioinformatics"},{"key":"2019100807483906600_bbx136-B44","doi-asserted-by":"crossref","first-page":"275","DOI":"10.1186\/1471-2105-15-275","article-title":"miRPlant: an integrated tool for identification of plant miRNA from RNA sequencing data","volume":"15","author":"An","year":"2014","journal-title":"BMC Bioinformatics"},{"key":"2019100807483906600_bbx136-B45","doi-asserted-by":"crossref","first-page":"370","DOI":"10.1186\/s12859-015-0798-3","article-title":"miRA: adaptable novel miRNA identification in plants using small RNA sequencing data","volume":"16","author":"Evers","year":"2015","journal-title":"BMC Bioinformatics"},{"issue":"1","key":"2019100807483906600_bbx136-B46","doi-asserted-by":"crossref","first-page":"163","DOI":"10.1101\/gr.123547.111","article-title":"High-resolution experimental and computational profiling of tissue-specific known and novel miRNAs in Arabidopsis","volume":"22","author":"Breakfield","year":"2012","journal-title":"Genome Res"},{"key":"2019100807483906600_bbx136-B47","doi-asserted-by":"crossref","first-page":"2837","DOI":"10.1093\/bioinformatics\/btu380","article-title":"miR-PREFeR: an accurate, fast and easy-to-use plant miRNA prediction tool using small RNA-Seq data","volume":"30","author":"Lei","year":"2014","journal-title":"Bioinformatics"},{"key":"2019100807483906600_bbx136-B48","doi-asserted-by":"crossref","first-page":"2446","DOI":"10.1093\/bioinformatics\/btx210","article-title":"miRCat2: accurate prediction of plant and animal microRNAs from next-generation sequencing datasets","volume":"33","author":"Paicu","year":"2017","journal-title":"Bioinformatics"},{"issue":"6","key":"2019100807483906600_bbx136-B49","doi-asserted-by":"crossref","first-page":"e66857","DOI":"10.1371\/journal.pone.0066857","article-title":"miReader: discovering novel miRNAs in species without sequenced genome","volume":"8","author":"Ashwani","year":"2013","journal-title":"PLoS One"},{"issue":"2","key":"2019100807483906600_bbx136-B50","doi-asserted-by":"crossref","first-page":"W114","DOI":"10.1093\/nar\/gkn297","article-title":"pssRNAMiner: a plant short small RNA regulatory cascade analysis server","volume":"36","author":"Dai","year":"2008","journal-title":"Nucl Acids Res"},{"key":"2019100807483906600_bbx136-B51","doi-asserted-by":"crossref","first-page":"2698","DOI":"10.1093\/bioinformatics\/bts496","article-title":"Shortran: a pipeline for small RNA-seq data analysis","volume":"28","author":"Gupta","year":"2012","journal-title":"Bioinformatics"},{"issue":"7","key":"2019100807483906600_bbx136-B52","doi-asserted-by":"crossref","first-page":"1045","DOI":"10.1093\/bioinformatics\/btt746","article-title":"tasiRNAdb: a database of ta-siRNA regulatory pathways","volume":"30","author":"Zhang","year":"2014","journal-title":"Bioinformatics"},{"key":"2019100807483906600_bbx136-B53","doi-asserted-by":"crossref","first-page":"284","DOI":"10.1093\/bioinformatics\/btu628","article-title":"PhaseTank: genome-wide computational identification of phasiRNAs and their regulatory cascades","volume":"31","author":"Guo","year":"2015","journal-title":"Bioinformatics"},{"key":"2019100807483906600_bbx136-B54","doi-asserted-by":"crossref","first-page":"1730","DOI":"10.1101\/gr.149310.112","article-title":"Integrated detection of natural antisense transcripts using strand-specific RNA sequencing data","volume":"23","author":"Li","year":"2013","journal-title":"Genome Res"},{"key":"2019100807483906600_bbx136-B55","doi-asserted-by":"crossref","first-page":"21666","DOI":"10.1038\/srep21666","article-title":"NATpipe: an integrative pipeline for systematical discovery of natural antisense transcripts (NATs) and phase-distributed nat-siRNAs from de novo assembled transcriptomes","volume":"6","author":"Yu","year":"2016","journal-title":"Sci Rep"},{"issue":"8","key":"2019100807483906600_bbx136-B56","doi-asserted-by":"crossref","first-page":"5270","DOI":"10.1093\/nar\/gku157","article-title":"A non-canonical plant microRNA target site","volume":"42","author":"Brousse","year":"2014","journal-title":"Nucleic Acids Rese"},{"issue":"13","key":"2019100807483906600_bbx136-B57","doi-asserted-by":"crossref","first-page":"e103","DOI":"10.1093\/nar\/gks277","article-title":"PAREsnip: a tool for rapid genome-wide discovery of small RNA\/target interactions evidenced through degradome sequencing","volume":"40","author":"Folkes","year":"2012","journal-title":"Nucl Acids Res"},{"key":"2019100807483906600_bbx136-B58","doi-asserted-by":"crossref","first-page":"891","DOI":"10.1111\/j.1365-313X.2012.04922.x","article-title":"SoMART: a webserver for plant miRNA, tasiRNA and target gene analysis","volume":"70","author":"Li","year":"2012","journal-title":"Plant J"},{"key":"2019100807483906600_bbx136-B59","doi-asserted-by":"crossref","first-page":"e28","DOI":"10.1093\/nar\/gkr1092","article-title":"SeqTar: an effective method for identifying microRNA guided cleavage sites from degradome of polyadenylated transcripts in plants","volume":"40","author":"Zheng","year":"2012","journal-title":"Nucl Acids Res"},{"key":"2019100807483906600_bbx136-B60","doi-asserted-by":"crossref","first-page":"18901","DOI":"10.1038\/srep18901","article-title":"miRNA Digger: a comprehensive pipeline for genome-wide novel miRNA mining","volume":"6","author":"Yu","year":"2016","journal-title":"Sci Rep"},{"key":"2019100807483906600_bbx136-B61","doi-asserted-by":"crossref","first-page":"W155","DOI":"10.1093\/nar\/gkr319","article-title":"psRNATarget: a plant small RNA target analysis server","volume":"39","author":"Dai","year":"2011","journal-title":"Nucl Acids Res"},{"key":"2019100807483906600_bbx136-B62","doi-asserted-by":"crossref","first-page":"1566","DOI":"10.1093\/bioinformatics\/btq233","article-title":"TAPIR, a web server for the prediction of plant microRNA targets, including target mimics","volume":"26","author":"Bonnet","year":"2010","journal-title":"Bioinformatics"},{"key":"2019100807483906600_bbx136-B63","doi-asserted-by":"crossref","first-page":"51","DOI":"10.1007\/978-1-60327-005-2_4","article-title":"miRNA target prediction in plants","volume":"592","author":"Fahlgren","year":"2010","journal-title":"Methods Mol Biol"},{"key":"2019100807483906600_bbx136-B64","doi-asserted-by":"crossref","first-page":"3002","DOI":"10.1093\/bioinformatics\/btq568","article-title":"Target-align: a tool for plant microRNA target identification","volume":"26","author":"Xie","year":"2010","journal-title":"Bioinformatics"},{"key":"2019100807483906600_bbx136-B65","doi-asserted-by":"crossref","first-page":"W22","DOI":"10.1093\/nar\/gks554","article-title":"PsRobot: a web-based plant small RNA meta-analysis toolbox","volume":"40","author":"Wu","year":"2012","journal-title":"Nucl Acids Res"},{"issue":"1","key":"2019100807483906600_bbx136-B66","doi-asserted-by":"crossref","first-page":"636","DOI":"10.1186\/1471-2164-12-636","article-title":"Employing machine learning for reliable miRNA target identification in plants","volume":"12","author":"Jha","year":"2011","journal-title":"BMC Genomics"},{"issue":"7","key":"2019100807483906600_bbx136-B67","doi-asserted-by":"crossref","first-page":"e103181","DOI":"10.1371\/journal.pone.0103181","article-title":"Plant microRNA-target interaction identification model based on the integration of prediction tools and support vector machine","volume":"9","author":"Meng","year":"2014","journal-title":"PLoS One"},{"key":"2019100807483906600_bbx136-B68","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1016\/j.ymeth.2015.04.003","article-title":"PlantMirnaT: miRNA and mRNA integrated analysis fully utilizing characteristics of plant sequencing data","volume":"83","author":"Rhee","year":"2015","journal-title":"Methods"},{"issue":"2","key":"2019100807483906600_bbx136-B69","doi-asserted-by":"crossref","first-page":"290","DOI":"10.1093\/bioinformatics\/btu633","article-title":"MTide: an integrated tool for the identification of miRNA\u2013target interaction in plants","volume":"31","author":"Zhang","year":"2015","journal-title":"Bioinformatics"},{"key":"2019100807483906600_bbx136-B70","doi-asserted-by":"crossref","first-page":"e139","DOI":"10.1093\/nar\/gku693","article-title":"sPARTA: a parallelized pipeline for integrated analysis of plant miRNA and cleaved mRNA data sets, including new miRNA target-identification software","volume":"42","author":"Kakrana","year":"2015","journal-title":"Nucleic Acids Res"},{"key":"2019100807483906600_bbx136-B71","unstructured":"Ding\n              J\n            , YuS, OhlerU, et al. imiRTP: an integrated method to identifying miRNA-target interactions in Arabidopsis thaliana. In: IEEE International Conference on Bioinformatics and Biomedicine. 2011, Atlanta, GA, USA: IEEE, pp. 100\u20134."},{"issue":"1","key":"2019100807483906600_bbx136-B72","first-page":"D152","article-title":"miRBase: integrating microRNA annotation and deep-sequencing data","volume":"39","author":"Kozomara","year":"2001","journal-title":"Nucl Acids Res"},{"issue":"1","key":"2019100807483906600_bbx136-B73","doi-asserted-by":"crossref","first-page":"D1187","DOI":"10.1093\/nar\/gkr823","article-title":"PlantNATsDB: a comprehensive database of plant natural antisense transcripts","volume":"40","author":"Chen","year":"2012","journal-title":"Nucl Acids Res"},{"issue":"3","key":"2019100807483906600_bbx136-B74","doi-asserted-by":"crossref","first-page":"403","DOI":"10.1016\/S0022-2836(05)80360-2","article-title":"Basic local alignment search tool","volume":"215","author":"Altschul","year":"1990","journal-title":"J Mol Biol"},{"key":"2019100807483906600_bbx136-B75","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1186\/1471-2164-10-155","article-title":"Bioinformatics analysis suggests base modification of tRNA and miRNA in Arabidopsis thaliana","volume":"10","author":"Iida","year":"2009","journal-title":"BMC Genomics"},{"key":"2019100807483906600_bbx136-B76","doi-asserted-by":"crossref","first-page":"2461","DOI":"10.1093\/nar\/gkp093","article-title":"Meta-analysis of small RNA-sequencing errors reveals ubiquitous post-transcriptional RNA modifications","volume":"37","author":"Ebhardt","year":"2009","journal-title":"Nucl Acids Res"},{"key":"2019100807483906600_bbx136-B77","doi-asserted-by":"crossref","first-page":"D136","DOI":"10.1093\/nar\/gkn766","article-title":"Rfam: updates to the RNA families database","volume":"37","author":"Gardner","year":"2009","journal-title":"Nucl Acids Res"},{"key":"2019100807483906600_bbx136-B78","doi-asserted-by":"crossref","first-page":"3186","DOI":"10.1105\/tpc.108.064311","article-title":"Criteria for annotation of plant microRNAs","volume":"20","author":"Meyers","year":"2008","journal-title":"Plant Cell"},{"key":"2019100807483906600_bbx136-B79","doi-asserted-by":"crossref","first-page":"e0150933.","DOI":"10.1371\/journal.pone.0150933","article-title":"Characterization of small RNAs derived from tRNAs, rRNAs and snoRNAs and their response to heat stress in wheat seedlings","volume":"11","author":"Wang","year":"2016","journal-title":"PLoS One"},{"key":"2019100807483906600_bbx136-B80","doi-asserted-by":"crossref","first-page":"1754","DOI":"10.1093\/bioinformatics\/btp324","article-title":"Fast and accurate short read alignment with Burrows-Wheeler transform","volume":"25","author":"Li","year":"2009","journal-title":"Bioinformatics"},{"issue":"3","key":"2019100807483906600_bbx136-B81","doi-asserted-by":"crossref","first-page":"R25","DOI":"10.1186\/gb-2009-10-3-r25","article-title":"Ultrafast and memory-efficient alignment of short DNA sequences to the human genome","volume":"10","author":"Langmead","year":"2009","journal-title":"Genome Biol"},{"issue":"2","key":"2019100807483906600_bbx136-B82","doi-asserted-by":"crossref","first-page":"243","DOI":"10.1111\/j.1365-313X.2006.02697.x","article-title":"Conservation and divergence of plant microRNA genes","volume":"46","author":"Zhang","year":"2006","journal-title":"Plant J"},{"key":"2019100807483906600_bbx136-B83","doi-asserted-by":"crossref","first-page":"2419","DOI":"10.1093\/nar\/gkp145","article-title":"Current tools for the identification of miRNA genes and their targets","volume":"37","author":"Mendes","year":"2009","journal-title":"Nucl Acids Res"},{"key":"2019100807483906600_bbx136-B84","doi-asserted-by":"crossref","first-page":"81","DOI":"10.3389\/fgene.2013.00081","article-title":"A review of computational tools in microRNA discovery","volume":"4","author":"Gomes","year":"2013","journal-title":"Front Genet"},{"key":"2019100807483906600_bbx136-B85","doi-asserted-by":"crossref","first-page":"310","DOI":"10.1186\/1471-2105-6-310","article-title":"Classification of real and pseudo microRNA precursors using local structure-sequence features and support vector machine","volume":"6","author":"Xue","year":"2005","journal-title":"BMC Bioinformatics"},{"key":"2019100807483906600_bbx136-B86","doi-asserted-by":"crossref","first-page":"989","DOI":"10.1093\/bioinformatics\/btp107","article-title":"MicroPred: effective classification of pre-miRNAs for human miRNA gene prediction","volume":"25","author":"Batuwita","year":"2009","journal-title":"Bioinformatics"},{"key":"2019100807483906600_bbx136-B87","doi-asserted-by":"crossref","first-page":"D68","DOI":"10.1093\/nar\/gkt1181","article-title":"miRBase: annotating high confidence microRNAs using deep sequencing data","volume":"42","author":"Kozomara","year":"2014","journal-title":"Nucleic Acids Res"},{"key":"2019100807483906600_bbx136-B88","doi-asserted-by":"crossref","first-page":"407","DOI":"10.1038\/nbt1394","article-title":"Discovering microRNAs from deep sequencing data using miRDeep","volume":"26","author":"Friedlander","year":"2008","journal-title":"Nat Biotechnol"},{"issue":"9","key":"2019100807483906600_bbx136-B89","doi-asserted-by":"crossref","first-page":"3318","DOI":"10.1073\/pnas.0611119104","article-title":"Bioinformatic prediction and experimental validation of a microRNA-directed tandem trans-acting siRNA cascade in Arabidopsis","volume":"104","author":"Chen","year":"2007","journal-title":"Proc Natl Acad Sci USA"},{"issue":"19","key":"2019100807483906600_bbx136-B90","doi-asserted-by":"crossref","first-page":"2252","DOI":"10.1093\/bioinformatics\/btn428","article-title":"A toolkit for analyzing large-scale plant small RNA datasets","volume":"24","author":"Moxon","year":"2008","journal-title":"Bioinformatics"},{"key":"2019100807483906600_bbx136-B91","doi-asserted-by":"crossref","first-page":"R30","DOI":"10.1186\/gb-2005-6-4-r30","article-title":"Genome-wide prediction and identification of cis-natural antisense transcripts in Arabidopsis thaliana","volume":"6","author":"Wang","year":"2005","journal-title":"Genome Biol"},{"issue":"2","key":"2019100807483906600_bbx136-B92","doi-asserted-by":"crossref","first-page":"88","DOI":"10.1016\/j.tibs.2003.12.002","article-title":"In search of antisense","volume":"29","author":"Lavorgna","year":"2004","journal-title":"Trends Biochem Sci"},{"key":"2019100807483906600_bbx136-B93","doi-asserted-by":"crossref","first-page":"R5","DOI":"10.1186\/gb-2003-5-1-r5","article-title":"Antisense transcripts with rice full-length cDNAs","volume":"5","author":"Osato","year":"2003","journal-title":"Genome Biol"},{"issue":"1","key":"2019100807483906600_bbx136-B94","doi-asserted-by":"crossref","first-page":"70","DOI":"10.1101\/gr.084806.108","article-title":"Genome-wide identification and analysis of small RNAs originated from natural antisense transcripts in Oryza sativa","volume":"19","author":"Zhou","year":"2009","journal-title":"Genome Res"},{"key":"2019100807483906600_bbx136-B95","doi-asserted-by":"crossref","first-page":"R51","DOI":"10.1186\/gb-2005-6-6-r51","article-title":"Natural antisense transcripts with coding capacity in Arabidopsis may have a regulatory role that is not linked to double-stranded RNA degradation","volume":"6","author":"Jen","year":"2005","journal-title":"Genome Biol"},{"issue":"22","key":"2019100807483906600_bbx136-B96","doi-asserted-by":"crossref","first-page":"2657","DOI":"10.1093\/bioinformatics\/btn193","article-title":"RNAplex: a fast tool for RNA-RNA interaction search","volume":"24","author":"Tafer","year":"2008","journal-title":"Bioinformatics"},{"key":"2019100807483906600_bbx136-B97","doi-asserted-by":"crossref","first-page":"e1002474","DOI":"10.1371\/journal.pgen.1002474","article-title":"Gene expression and stress response mediated by the epigenetic regulation of a transposable element small RNA","volume":"8","author":"McCue","year":"2012","journal-title":"PLoS Genet"},{"key":"2019100807483906600_bbx136-B98","doi-asserted-by":"crossref","first-page":"116","DOI":"10.1104\/pp.113.216481","article-title":"The initiation of epigenetic silencing of active transposable elements is triggered by RDR6 and 21-22 nucleotide small interfering RNAs","volume":"162","author":"Nuthikattu","year":"2013","journal-title":"Plant Physiol"},{"key":"2019100807483906600_bbx136-B99","doi-asserted-by":"crossref","first-page":"352","DOI":"10.1016\/j.cell.2012.10.054","article-title":"Comprehensive analysis of silencing mutants reveals complex regulation of the Arabidopsis methylome","volume":"152","author":"Stroud","year":"2013","journal-title":"Cell"},{"key":"2019100807483906600_bbx136-B100","doi-asserted-by":"crossref","first-page":"465","DOI":"10.1016\/j.molcel.2010.03.008","article-title":"DNA methylation mediated by a microRNA pathway","volume":"38","author":"Wu","year":"2010","journal-title":"Mol Cell"},{"key":"2019100807483906600_bbx136-B101","doi-asserted-by":"crossref","first-page":"1029","DOI":"10.1038\/ng.2703","article-title":"Reconstructing de novo silencing of an active plant retrotransposon","volume":"45","author":"Mari-Ordonez","year":"2013","journal-title":"Nat Genet"},{"issue":"29","key":"2019100807483906600_bbx136-B102","doi-asserted-by":"crossref","first-page":"E4248","DOI":"10.1073\/pnas.1607851113","article-title":"Methylation interactions in Arabidopsis hybrids require RNA-directed DNA methylation and are influenced by genetic variation","volume":"113","author":"Zhang","year":"2016","journal-title":"Proc Natl Acad Sci USA"},{"key":"2019100807483906600_bbx136-B103","doi-asserted-by":"crossref","first-page":"523","DOI":"10.1016\/j.cell.2008.03.029","article-title":"Highly integrated single-base resolution maps of the epigenome in Arabidopsis","volume":"133","author":"Lister","year":"2008","journal-title":"Cell"},{"key":"2019100807483906600_bbx136-B104","doi-asserted-by":"crossref","first-page":"259","DOI":"10.1105\/tpc.107.056879","article-title":"High-resolution mapping of epigenetic modifications of the rice genome uncovers interplay between DNA methylation, histone methylation, and gene expression","volume":"20","author":"Li","year":"2008","journal-title":"Plant Cell"},{"key":"2019100807483906600_bbx136-B105","doi-asserted-by":"crossref","first-page":"411","DOI":"10.1038\/nature13069","article-title":"MiRNAs trigger widespread epigenetically activated siRNAs from transposons in Arabidopsis","volume":"508","author":"Creasey","year":"2014","journal-title":"Nature"},{"key":"2019100807483906600_bbx136-B106","doi-asserted-by":"crossref","first-page":"1605","DOI":"10.1105\/tpc.003210","article-title":"Endogenous and silencing-associated small RNAs in plants","volume":"14","author":"Llave","year":"2002","journal-title":"Plant Cell"},{"issue":"5880","key":"2019100807483906600_bbx136-B107","doi-asserted-by":"crossref","first-page":"1185","DOI":"10.1126\/science.1159151","article-title":"Widespread translational inhibition by plant miRNAs and siRNAs","volume":"320","author":"Brodersen","year":"2008","journal-title":"Science"},{"key":"2019100807483906600_bbx136-B108","doi-asserted-by":"crossref","first-page":"591","DOI":"10.1016\/j.molcel.2013.10.033","article-title":"Molecular insights into microRNA-mediated translational repression in plants","volume":"52","author":"Iwakawa","year":"2013","journal-title":"Mol Cell"},{"key":"2019100807483906600_bbx136-B109","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1016\/0022-2836(81)90087-5","article-title":"Identification of common molecular subsequences","volume":"147","author":"Smith","year":"1981","journal-title":"J Mol Biol"},{"key":"2019100807483906600_bbx136-B110","doi-asserted-by":"crossref","first-page":"26.","DOI":"10.1186\/1748-7188-6-26","article-title":"ViennaRNA package 2.0","volume":"6","author":"Lorenz","year":"2011","journal-title":"Algorithms Mol Biol"},{"key":"2019100807483906600_bbx136-B111","doi-asserted-by":"crossref","first-page":"W451","DOI":"10.1093\/nar\/gkl243","article-title":"RNAhybrid: microRNA target prediction easy, fast and flexible","volume":"34","author":"Kruger","year":"2006","journal-title":"Nucl Acids Res"},{"key":"2019100807483906600_bbx136-B112","doi-asserted-by":"crossref","first-page":"348","DOI":"10.1186\/1471-2164-15-348","article-title":"A comparison of performance of plant miRNA target prediction tools and the characterization of features for genome-wide target prediction","volume":"15","author":"Srivastava","year":"2014","journal-title":"BMC Genomics"},{"key":"2019100807483906600_bbx136-B113","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1093\/nar\/gkr688","article-title":"miRDeep2 accurately identifies known and hundreds of novel microRNA genes in seven animal clades","volume":"40","author":"Friedlander","year":"2012","journal-title":"Nucl Acids Res"},{"key":"2019100807483906600_bbx136-B114","first-page":"173575","article-title":"Learning sequence patterns of AGO-sRNA affinity from high-throughput sequencing libraries to improve in silico functional small RNA detection and classification in plants","author":"Morgado","year":"2107","journal-title":"bioRxiv"}],"container-title":["Briefings in Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/academic.oup.com\/bib\/article-pdf\/20\/4\/1181\/30119545\/bbx136.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"http:\/\/academic.oup.com\/bib\/article-pdf\/20\/4\/1181\/30119545\/bbx136.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,10,8]],"date-time":"2019-10-08T07:49:44Z","timestamp":1570520984000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bib\/article\/20\/4\/1181\/4558649"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,10,20]]},"references-count":114,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2017,10,20]]},"published-print":{"date-parts":[[2019,7,19]]}},"URL":"https:\/\/doi.org\/10.1093\/bib\/bbx136","relation":{},"ISSN":["1467-5463","1477-4054"],"issn-type":[{"value":"1467-5463","type":"print"},{"value":"1477-4054","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2019,7]]},"published":{"date-parts":[[2017,10,20]]}}}