MicroRNA - Experimental Detection and Manipulation of MiRNA

Experimental Detection and Manipulation of MiRNA

While researchers have focused on the study of miRNA expression in physiological and pathological processes, various technical variables related to microRNA isolation have emerged. The stability of the stored miRNA samples has often been questioned. MicroRNAs are degraded much more easily than mRNAs, partly due to their length, but also because of the ubiquitously present RNases. This makes it necessary to cool samples on ice and use RNase-free equipment whenever working with microRNAs.

MicroRNA expression can be quantified in a two-step polymerase chain reaction process of modified RT-PCR followed by quantitative real-time PCR. Variations of this method achieve absolute or relative quantification. miRNAs can also be hybridized to microarrays, slides or chips with probes to hundreds or thousands of miRNA targets, so that relative levels of miRNAs can be determined in different samples. MicroRNAs can be both discovered and profiled by high-throughput sequencing methods (MicroRNA Sequencing). The activity of an miRNA can be experimentally inhibited using a locked nucleic acid (LNA) oligo, a Morpholino oligo or a 2'-O-methyl RNA oligo. Additionally, a specific miRNA can be silenced by a complementary antagomir. MicroRNA maturation can be inhibited at several points by steric-blocking oligos. The miRNA target site of an mRNA transcript can also be blocked by a steric-blocking oligo. For the “in situ” detection of miRNA, LNA or Morpholino probes can be used. The locked conformation of LNA results in enhanced hybridization properties and increases sensitivity and selectivity, making it ideal for detection of short miRNA.

High-throughput quantification of miRNAs is often difficult and prone to errors, for the larger variance (compared to mRNAs) that comes with the methodological problems. mRNA-expression is therefore often analyzed as well to check for miRNA-effects in their levels (e. g. in ). To pair mRNA- and miRNA-data, databases can be used which predict miRNA-targets based on their base sequence. While this is usually done after miRNAs of interest have been detected (e. g. because of high expression levels), ideas for analysis tools that integrate mRNA- and miRNA-expression information have been proposed.

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