Lee RC, Feinbaum RL, Ambros V. The C. elegans heterochronic gene lin-4 encodes small RNAs with antisense complementarity to lin-14. Cell. 1993;75(5):843–54.
Article
CAS
Google Scholar
Wightman B, Ha I, Ruvkun G. Posttranscriptional regulation of the heterochronic gene lin-14 by lin-4 mediates temporal pattern formation in C. elegans. Cell. 1993;75(5):855–62.
Article
CAS
Google Scholar
Ambros V. The functions of animal microRNAs. Nature. 2004;431(7006):350–5.
Article
CAS
Google Scholar
Bartel DP. MicroRNAs: genomics, biogenesis, mechanism and function. Cell. 2004;116(2):281–97.
Article
CAS
Google Scholar
Vrijens K, Bollati V, Nawrot TS. MicroRNAs as potential signatures of environmental exposure or effect: a systematic review. Environ Health Perspect. 2015;123(5):399–411.
Article
CAS
Google Scholar
Kondkar AA, Abu-Amero KK. Utility of circulating microRNAs as clinical biomarkers for cardiovascular diseases. Biomed Res Int. 2015;2015:821823.
Article
Google Scholar
Laterza OF, Scott MG, Garrett-Engele PW, Korenblat KM, Lockwood CM. Circulating miR-122 as a potential biomarker of liver disease. Biomark Med. 2013;7(2):205–10.
Article
CAS
Google Scholar
Wang K, Zhang S, Marzolf B, Troisch P, Brightman A, Hu Z, Hood LE, Galas DJ. Circulating microRNAs, potential biomarkers for drug-induced liver injury. Proc Natl Acad Sci U S A. 2009;106(11):4402–7.
Article
CAS
Google Scholar
Shifeng H, Danni W, Pu C, Ping Y, Ju C, Liping Z. Circulating liver-specific miR-122 as a novel potential biomarker for diagnosis of cholestatic liver injury. PLoS One. 2013;8(9):e73133.
Article
Google Scholar
Ludwig N, Leidinger P, Becker K, Backes C, Fehlmann T, Pallasch C, Rheinheimer S, Meder B, Stahler C, Meese E, et al. Distribution of miRNA expression across human tissues. Nucleic Acids Res. 2016;44(8):3865–77.
Article
CAS
Google Scholar
Koenig EM, Fisher C, Bernard H, Wolenski FS, Gerrein J, Carsillo M, Gallacher M, Tse A, Peters R, Smith A, et al. The beagle dog MicroRNA tissue atlas: identifying translatable biomarkers of organ toxicity. BMC Genomics. 2016;17:649.
Article
Google Scholar
Betel D, Wilson M, Gabow A, Marks DS, Sander C. The microRNA.org resource: targets and expression. Nucleic Acids Res. 2008;36(Database issue):D149–53.
CAS
PubMed
Google Scholar
Minami K, Uehara T, Morikawa Y, Omura K, Kanki M, Horinouchi A, Ono A, Yamada H, Ohno Y, Urushidani T. miRNA expression atlas in male rat. Sci Data. 2014;1:140005.
Article
CAS
Google Scholar
Panwar B, Omenn GS, Guan Y. miRmine: a database of human miRNA expression profiles. Bioinformatics. 2017;33(10):1554–60.
CAS
PubMed
PubMed Central
Google Scholar
Li SC, Chan WC, Hu LY, Lai CH, Hsu CN, Lin WC. Identification of homologous microRNAs in 56 animal genomes. Genomics. 2010;96(1):1–9.
Article
CAS
Google Scholar
Seqc C. A comprehensive assessment of RNA-seq accuracy, reproducibility and information content by the sequencing quality control consortium. Nat Biotechnol. 2014;32(9):903–14.
Article
Google Scholar
Wang C, Gong B, Bushel PR, Thierry-Mieg J, Thierry-Mieg D, Xu J, Fang H, Hong H, Shen J, Su Z, et al. The concordance between RNA-seq and microarray data depends on chemical treatment and transcript abundance. Nat Biotechnol. 2014;32(9):926–32.
Article
CAS
Google Scholar
Smith A, Calley J, Mathur S, Qian HR, Wu H, Farmen M, Caiment F, Bushel PR, Li J, Fisher C, et al. The rat microRNA body atlas; evaluation of the microRNA content of rat organs through deep sequencing and characterization of pancreas enriched miRNAs as biomarkers of pancreatic toxicity in the rat and dog. BMC Genomics. 2016;17:694.
Article
Google Scholar
Brunet JP, Tamayo P, Golub TR, Mesirov JP. Metagenes and molecular pattern discovery using matrix factorization. Proc Natl Acad Sci U S A. 2004;101(12):4164–9.
Article
CAS
Google Scholar
Edgar R, Domrachev M, Lash AE. Gene expression omnibus: NCBI gene expression and hybridization array data repository. Nucleic Acids Res. 2002;30(1):207–10.
Article
CAS
Google Scholar
Barrett T, Wilhite SE, Ledoux P, Evangelista C, Kim IF, Tomashevsky M, Marshall KA, Phillippy KH, Sherman PM, Holko M, et al. NCBI GEO: archive for functional genomics data sets--update. Nucleic Acids Res. 2013;41(Database issue):D991–5.
CAS
PubMed
Google Scholar
Friedlander MR, Chen W, Adamidi C, Maaskola J, Einspanier R, Knespel S, Rajewsky N. Discovering microRNAs from deep sequencing data using miRDeep. Nat Biotechnol. 2008;26(4):407–15.
Article
Google Scholar
Griffiths-Jones S. The microRNA registry. Nucleic Acids Res. 2004;32(Database issue):D109–11.
Article
CAS
Google Scholar
Griffiths-Jones S, Grocock RJ, van Dongen S, Bateman A. Enright AJ: miRBase: microRNA sequences, targets and gene nomenclature. Nucleic Acids Res. 2006;34(Database issue):D140–4.
Article
CAS
Google Scholar
Griffiths-Jones S, Saini HK, van Dongen S. Enright AJ: miRBase: tools for microRNA genomics. Nucleic Acids Res. 2008;36(Database issue):D154–8.
CAS
PubMed
Google Scholar
Kozomara A, Griffiths-Jones S. miRBase: integrating microRNA annotation and deep-sequencing data. Nucleic Acids Res. 2011;39(Database issue):D152–7.
Article
CAS
Google Scholar
Kozomara A, Griffiths-Jones S. miRBase: annotating high confidence microRNAs using deep sequencing data. Nucleic Acids Res. 2014;42(Database issue):D68–73.
Article
CAS
Google Scholar
Li H, Durbin R. Fast and accurate short read alignment with burrows-wheeler transform. Bioinformatics. 2009;25(14):1754–60.
Article
CAS
Google Scholar
Lund SP, Nettleton D, McCarthy DJ, Smyth GK. Detecting differential expression in RNA-sequence data using quasi-likelihood with shrunken dispersion estimates. Stat Appl Genet Mol Biol. 2012;11(5):Article 8.
Yates A, Akanni W, Amode MR, Barrell D, Billis K, Carvalho-Silva D, Cummins C, Clapham P, Fitzgerald S, Gil L, et al. Ensembl 2016. Nucleic Acids Res. 2016;44(D1):D710–6.
Article
CAS
Google Scholar
Prufer K, Stenzel U, Dannemann M, Green RE, Lachmann M, Kelso J. PatMaN: rapid alignment of short sequences to large databases. Bioinformatics. 2008;24(13):1530–1.
Article
Google Scholar
Robinson MD, Oshlack A. A scaling normalization method for differential expression analysis of RNA-seq data. Genome Biol. 2010;11(3):R25.
Article
Google Scholar
Axmark D, Widenius M. MySQL 5.7 reference manual; 2015.
Google Scholar
Garmire LX, Subramaniam S. Evaluation of normalization methods in mammalian microRNA-Seq data. RNA. 2012;18(6):1279–88.
Article
CAS
Google Scholar
Zhou X, Oshlack A, Robinson MD. miRNA-Seq normalization comparisons need improvement. RNA. 2013;19(6):733–4.
Article
CAS
Google Scholar
Tam S, Tsao MS, McPherson JD. Optimization of miRNA-seq data preprocessing. Brief Bioinform. 2015;16(6):950–63.
Article
CAS
Google Scholar
Beckers M, Mohorianu I, Stocks M, Applegate C, Dalmay T, Moulton V. Comprehensive processing of high-throughput small RNA sequencing data including quality checking, normalization, and differential expression analysis using the UEA sRNA workbench. RNA. 2017;23(6):823–35.
Article
CAS
Google Scholar
Wong N, Wang X. miRDB: an online resource for microRNA target prediction and functional annotations. Nucleic Acids Res. 2015;43(Database issue):D146–52.
Article
CAS
Google Scholar
R. A language and environment for statistical computing. R Foundation for statistical computing. Austria: Vienna; 2013.
Google Scholar
Smyth GK. Linear models and empirical bayes methods for assessing differential expression in microarray experiments. Stat Appl Genet Mol Biol. 2004;3(1):Article3.
Article
Google Scholar
Gentleman R. Bioinformatics and computational biology solutions using R and Bioconductor. New York: springer science+business Media; 2005.
Book
Google Scholar
Yanai I, Benjamin H, Shmoish M, Chalifa-Caspi V, Shklar M, Ophir R, Bar-Even A, Horn-Saban S, Safran M, Domany E, et al. Genome-wide midrange transcription profiles reveal expression level relationships in human tissue specification. Bioinformatics. 2005;21(5):650–9.
Article
CAS
Google Scholar
Jazbutyte V, Thum T. MicroRNA-21: from cancer to cardiovascular disease. Curr Drug Targets. 2010;11(8):926–35.
Article
CAS
Google Scholar
Church RJ, Otieno M, McDuffie JE, Singh B, Sonee M, Hall L, Watkins PB, Ellinger-Ziegelbauer H, Harrill AH. Beyond miR-122: identification of MicroRNA alterations in blood during a time course of hepatobiliary injury and biliary hyperplasia in rats. Toxicol Sci. 2016;150(1):3–14.
Article
CAS
Google Scholar
Jayaprakash AD, Jabado O, Brown BD, Sachidanandam R. Identification and remediation of biases in the activity of RNA ligases in small-RNA deep sequencing. Nucleic Acids Res. 2011;39(21):e141.
Article
CAS
Google Scholar
Sorefan K, Pais H, Hall AE, Kozomara A, Griffiths-Jones S, Moulton V, Dalmay T. Reducing ligation bias of small RNAs in libraries for next generation sequencing. Silence. 2012;3(1):4.
Article
CAS
Google Scholar