Sequence analysis Prediction of both conserved and nonconserved microRNA targets in animals

MOTIVATION MicroRNAs (miRNAs) are involved in many diverse biological processes and they may potentially regulate the functions of thousands of genes. However, one major issue in miRNA studies is the lack of bioinformatics programs to accurately predict miRNA targets. Animal miRNAs have limited sequence complementarity to their gene targets, which makes it challenging to build target prediction models with high specificity. RESULTS Here we present a new miRNA target prediction program based on support vector machines (SVMs) and a large microarray training dataset. By systematically analyzing public microarray data, we have identified statistically significant features that are important to target downregulation. Heterogeneous prediction features have been non-linearly integrated in an SVM machine learning framework for the training of our target prediction model, MirTarget2. About half of the predicted miRNA target sites in human are not conserved in other organisms. Our prediction algorithm has been validated with independent experimental data for its improved performance on predicting a large number of miRNA down-regulated gene targets. AVAILABILITY All the predicted targets were imported into an online database miRDB, which is freely accessible at http://mirdb.org.

[1]  A. Hatzigeorgiou,et al.  A combined computational-experimental approach predicts human microRNA targets. , 2004, Genes & development.

[2]  L. Lim,et al.  Transcripts Targeted by the MicroRNA-16 Family Cooperatively Regulate Cell Cycle Progression , 2007, Molecular and Cellular Biology.

[3]  Shyh-Huei Chen,et al.  A support vector machine approach for detecting gene‐gene interaction , 2008, Genetic epidemiology.

[4]  Y. Li,et al.  Incorporating structure to predict microRNA targets. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[5]  C. Burge,et al.  The Widespread Impact of Mammalian MicroRNAs on mRNA Repression and Evolution , 2005, Science.

[6]  J. Castle,et al.  Microarray analysis shows that some microRNAs downregulate large numbers of target mRNAs , 2005, Nature.

[7]  Gerald M Rubin,et al.  Pervasive regulation of Drosophila Notch target genes by GY-box-, Brd-box-, and K-box-class microRNAs. , 2005, Genes & development.

[8]  Lin He,et al.  MicroRNAs: small RNAs with a big role in gene regulation , 2004, Nature reviews genetics.

[9]  E. Lai.  Micro RNAs are complementary to 3′ UTR sequence motifs that mediate negative post-transcriptional regulation , 2002, Nature Genetics.

[10]  Michael Kertesz,et al.  The role of site accessibility in microRNA target recognition , 2007, Nature Genetics.

[11]  David L. Wheeler,et al.  GenBank , 2015, Nucleic Acids Res..

[12]  N. Rajewsky.  microRNA target predictions in animals , 2006, Nature Genetics.

[13]  Nikolas P. Galatsanos,et al.  A support vector machine approach for detection of microcalcifications , 2002, IEEE Transactions on Medical Imaging.

[14]  R. Russell,et al.  Principles of MicroRNA–Target Recognition , 2005, PLoS biology.

[15]  L. Lim,et al.  MicroRNA targeting specificity in mammals: determinants beyond seed pairing. , 2007, Molecular cell.

[16]  Stijn van Dongen,et al.  miRBase: microRNA sequences, targets and gene nomenclature , 2005, Nucleic Acids Res..

[17]  V. Ambros.  The functions of animal microRNAs , 2004, Nature.

[18]  Ivo L. Hofacker,et al.  Vienna RNA secondary structure server , 2003, Nucleic Acids Res..

[19]  Shuang Huang,et al.  Involvement of MicroRNA in AU-Rich Element-Mediated mRNA Instability , 2005, Cell.

[20]  E. Miska,et al.  How microRNAs control cell division, differentiation and death. , 2005, Current opinion in genetics & development.

[21]  Dennis B. Troup,et al.  NCBI GEO: mining tens of millions of expression profiles—database and tools update , 2006, Nucleic Acids Res..

[22]  K. Gunsalus,et al.  Combinatorial microRNA target predictions , 2005, Nature Genetics.

[23]  Yvonne Tay,et al.  A Pattern-Based Method for the Identification of MicroRNA Binding Sites and Their Corresponding Heteroduplexes , 2006, Cell.

[24]  Yong Zhao,et al.  Serum response factor regulates a muscle-specific microRNA that targets Hand2 during cardiogenesis , 2005, Nature.

[25]  A. Pasquinelli,et al.  Regulation by let-7 and lin-4 miRNAs Results in Target mRNA Degradation , 2005, Cell.

[26]  Anindya Dutta,et al.  The tumor suppressor microRNA let-7 represses the HMGA2 oncogene. , 2007, Genes & development.

[27]  Richard W. Carthew,et al.  Silence from within: Endogenous siRNAs and miRNAs , 2005, Cell.

[28]  Dang D. Long,et al.  Potent effect of target structure on microRNA function , 2007, Nature Structural &Molecular Biology.

[29]  A. Hatzigeorgiou,et al.  TarBase: A comprehensive database of experimentally supported animal microRNA targets. , 2005, RNA.

[30]  Anton J. Enright,et al.  MicroRNA targets in Drosophila , 2003, Genome Biology.

[31]  J. Kitzman,et al.  Determinants of targeting by endogenous and exogenous microRNAs and siRNAs. , 2007, RNA.

[32]  Julius Brennecke,et al.  Identification of Drosophila MicroRNA Targets , 2003, PLoS biology.

[33]  Mihaela Zavolan,et al.  Inference of miRNA targets using evolutionary conservation and pathway analysis , 2007, BMC Bioinformatics.

[34]  R. Russell,et al.  Animal MicroRNAs Confer Robustness to Gene Expression and Have a Significant Impact on 3′UTR Evolution , 2005, Cell.

[35]  Xiaowei Wang,et al.  Systematic identification of microRNA functions by combining target prediction and expression profiling , 2006, Nucleic acids research.

[36]  Byoung-Tak Zhang,et al.  miTarget: microRNA target gene prediction using a support vector machine , 2006, BMC Bioinformatics.

[37]  C. Burge,et al.  Conserved Seed Pairing, Often Flanked by Adenosines, Indicates that Thousands of Human Genes are MicroRNA Targets , 2005, Cell.

[38]  R. Giegerich,et al.  Fast and effective prediction of microRNA/target duplexes. , 2004, RNA.