Messenger RNAs (mRNAs) fulfil specific biological roles in cells and, thus, their expression may be adapted to suit specific circumstances. This is in part achieved through selective gene transcription and post-transcriptional events, the regulation of which must be tightly integrated and controlled. To comprehensively study the coordinated effects of transcriptional and post-transcriptional regulatory elements, and to obtain coherent results, it is advisable to use different methodologies. Adequately integrating the data derived from these distinct methodologies then becomes critical to elucidating the relationships between the coordinated cellular effects assayed, particularly when applied to normal and disease states. Such integrated studies are likely to be particularly useful to identify markers suitable for early detection of diseases and to devise strategies for therapeutic interventions. Throughout this chapter, we will focus on the methods currently available to analyse mRNA and microRNA (miRNA) expression, paying special attention to the influence of miRNAs on mRNA metabolism. We will introduce miARma-Seq, a comprehensive pipeline that facilitates the simultaneous integration of mRNA and miRNA expression data. For illustrative purposes, we include a case study that incorporates data from RNASeq and small-RNASeq, detailing all the steps necessary to define the differential expression of both mRNA- and miRNA-encoding genes. Finally, we explore the possible regulatory relationships that drive significant and potentially relevant changes in mRNA and miRNA gene expression.
Keywords: Integrative analysis; RNASeq analysis; Small RNASeq analysis; miRNA; miRNA-mRNA target prediction.
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