9. Detecting MicroRNA Signatures Using Gene Expression Analysis

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.