Detecting MicroRNA Signatures Using Gene Expression Analysis

  • Stijn van Dongen
  • Anton J. Enright


Small RNAs such as microRNAs (miRNAs) have been shown to play important roles in genetic regulation of plants and animals. In particular, the miRNAs of animals are capable of downregulating large numbers of genes by binding to and repressing target genes. Although large numbers of miRNAs have been cloned and sequenced, methods for analyzing their targets are far from perfect. Methods exist that can predict the likely binding sites of miRNAs in target transcripts using sequence alignment, thermodynamics or machine learning approaches. It has been widely illustrated that such de novo computational approaches suffer from high false-positive and false-negative error rates. In particular these approaches do not take into account expression information regarding the miRNA or its target transcript. In this chapter we describe the use of miRNA seed enrichment analysis approaches to this problem. In cases where gene or protein expression data are available, it is possible to detect the signature of miRNA binding events by looking for enrichment of microRNA seed binding motifs in sorted gene lists. In this chapter we introduce the concept of miRNA target analysis, the background to motif enrichment analysis, and a number of programs designed for this purpose. We focus on the Sylamer algorithm for miRNA seed enrichment analysis and its applications for miRNA target discovery with examples from real biological datasets.


Gene Ontology Gene List miRNA Target Seed Region Hypergeometric Distribution 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



AU-rich element


Berkeley Drosophila genome project


binding site enrichment detection


cap analysis gene expression


deoxyribonucleic acid


discovery of rank-imbalanced motifs




expressed sequence tag


Granger causality


green fluorescent protein


gene ontology


gene set enrichment analysis


Henrietta Lacks


highthroughput sequencing with crosslinking and immunoprecipitation


International Union of Pure and Applied Chemistry




multiple expectation maximization for motif elicitation


position-specific scoring matrix


position-specific weight matrix


regulatory element detection using correlation with expression


ribonucleic acid


RNA interference


regulatory sequence analysis tools


T-helper cell


untranslated regions


complementary DNA




logistic regression


messenger RNA




protein stable labeling by amino acids in cell culture


photoactivatable ribunocleoside enhanced-CLIP


small interfering RNA


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Copyright information

© Springer-Verlag 2014

Authors and Affiliations

  1. 1.Wellcome Trust Genome CampusEMBL – European Bioinformatics InstituteHinxtonUK
  2. 2.Wellcome Trust Genome CampusEMBL – European Bioinformatics InstituteHinxtonUK

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